{"abstract":"Calls on dividend payers are overpriced.","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":"Discounting the spot leg at the interest rate confuses the carry.","family":"w2-options_payoff_and_settlement-black-scholes-dividend-yield-call-spot-discounting","id":"FA-61551","implementations":{"attempt":{"sha256":"f7c806a5fb21e7c321d24b52fc5cbd34e476c23e4a8cf711dd5acc6462385249","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(-r * 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 call spot discounting 1', ['C', 110.0, 105.0, 0.0, 0.015, 0.35, 91], 9.987818], ['regression call spot discounting 2', ['C', 110.0, 100.0, 0.02, 0.03, 0.2, 30], 10.017783], ['partial repair probe 1', ['C', 100.0, 105.0, 0.05, 0.0, 0.1, 730], 8.348306], ['partial repair probe 2', ['C', 100.0, 95.0, 0.02, 0.0, 0.1, 365], 8.228981], ['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', 100.0, 105.0, 0.0, 0.0, 0.2, 7], 5.044601], ['normal control 2', ['P', 110.0, 100.0, 0.02, 0.015, 0.2, 0], 0.0]], [['regression call spot discounting 1', ['C', 110.0, 105.0, 0.0, 0.015, 0.35, 7], 5.441716], ['regression call spot discounting 2', ['C', 110.0, 95.0, 0.0, 0.015, 0.1, 182], 14.246408], ['partial repair probe 1', ['C', 90.0, 100.0, 0.05, 0.0, 0.2, 7], 5.1e-05], ['partial repair probe 2', ['C', 90.0, 95.0, 0.02, 0.0, 0.35, 182], 7.16504], ['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, 100.0, 0.0, 0.03, 0.1, 1], 10.007397], ['normal control 2', ['P', 100.0, 100.0, 0.0, 0.0, 0.2, 1], 0.41763]], [['regression call spot discounting 1', ['C', 110.0, 105.0, 0.05, 0.015, 0.1, 91], 6.250733], ['regression call spot discounting 2', ['C', 110.0, 100.0, 0.0, 0.03, 0.35, 365], 17.981981], ['partial repair probe 1', ['C', 110.0, 95.0, 0.05, 0.0, 0.2, 730], 26.930371], ['partial repair probe 2', ['C', 110.0, 95.0, 0.05, 0.0, 0.1, 91], 16.177886], ['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', 110.0, 100.0, 0.05, 0.0, 0.1, 0], 0.0], ['normal control 2', ['P', 90.0, 95.0, 0.0, 0.0, 0.2, 0], 5.0]], [['regression call spot discounting 1', ['C', 90.0, 95.0, 0.02, 0.015, 0.1, 730], 3.308995], ['regression call spot discounting 2', ['C', 110.0, 95.0, 0.05, 0.03, 0.1, 730], 18.216377], ['partial repair probe 1', ['C', 90.0, 100.0, 0.05, 0.0, 0.35, 730], 17.398625], ['partial repair probe 2', ['C', 110.0, 105.0, 0.02, 0.0, 0.2, 365], 12.482761], ['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, 0.02, 0.0, 0.2, 0], 0.0], ['normal control 2', ['P', 110.0, 105.0, 0.02, 0.015, 0.1, 1], 0.0]], [['regression call spot discounting 1', ['C', 100.0, 105.0, 0.02, 0.015, 0.1, 7], 7.8e-05], ['regression call spot discounting 2', ['C', 90.0, 100.0, 0.02, 0.015, 0.35, 7], 0.02433], ['partial repair probe 1', ['C', 100.0, 105.0, 0.02, 0.0, 0.2, 7], 0.04615], ['partial repair probe 2', ['C', 110.0, 105.0, 0.02, 0.0, 0.1, 182], 6.949255], ['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', 100.0, 100.0, 0.02, 0.015, 0.1, 0], 0.0], ['normal control 2', ['P', 110.0, 105.0, 0.05, 0.015, 0.2, 91], 1.934882]]]\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":"c256e0b9426ba9ed2cba234aad3c7a225019a4f99efa6d068270a35846fad820","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 * 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 call spot discounting 1', ['C', 110.0, 105.0, 0.0, 0.015, 0.35, 91], 9.987818], ['regression call spot discounting 2', ['C', 110.0, 100.0, 0.02, 0.03, 0.2, 30], 10.017783], ['partial repair probe 1', ['C', 100.0, 105.0, 0.05, 0.0, 0.1, 730], 8.348306], ['partial repair probe 2', ['C', 100.0, 95.0, 0.02, 0.0, 0.1, 365], 8.228981], ['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', 100.0, 105.0, 0.0, 0.0, 0.2, 7], 5.044601], ['normal control 2', ['P', 110.0, 100.0, 0.02, 0.015, 0.2, 0], 0.0]], [['regression call spot discounting 1', ['C', 110.0, 105.0, 0.0, 0.015, 0.35, 7], 5.441716], ['regression call spot discounting 2', ['C', 110.0, 95.0, 0.0, 0.015, 0.1, 182], 14.246408], ['partial repair probe 1', ['C', 90.0, 100.0, 0.05, 0.0, 0.2, 7], 5.1e-05], ['partial repair probe 2', ['C', 90.0, 95.0, 0.02, 0.0, 0.35, 182], 7.16504], ['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, 100.0, 0.0, 0.03, 0.1, 1], 10.007397], ['normal control 2', ['P', 100.0, 100.0, 0.0, 0.0, 0.2, 1], 0.41763]], [['regression call spot discounting 1', ['C', 110.0, 105.0, 0.05, 0.015, 0.1, 91], 6.250733], ['regression call spot discounting 2', ['C', 110.0, 100.0, 0.0, 0.03, 0.35, 365], 17.981981], ['partial repair probe 1', ['C', 110.0, 95.0, 0.05, 0.0, 0.2, 730], 26.930371], ['partial repair probe 2', ['C', 110.0, 95.0, 0.05, 0.0, 0.1, 91], 16.177886], ['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', 110.0, 100.0, 0.05, 0.0, 0.1, 0], 0.0], ['normal control 2', ['P', 90.0, 95.0, 0.0, 0.0, 0.2, 0], 5.0]], [['regression call spot discounting 1', ['C', 90.0, 95.0, 0.02, 0.015, 0.1, 730], 3.308995], ['regression call spot discounting 2', ['C', 110.0, 95.0, 0.05, 0.03, 0.1, 730], 18.216377], ['partial repair probe 1', ['C', 90.0, 100.0, 0.05, 0.0, 0.35, 730], 17.398625], ['partial repair probe 2', ['C', 110.0, 105.0, 0.02, 0.0, 0.2, 365], 12.482761], ['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, 0.02, 0.0, 0.2, 0], 0.0], ['normal control 2', ['P', 110.0, 105.0, 0.02, 0.015, 0.1, 1], 0.0]], [['regression call spot discounting 1', ['C', 100.0, 105.0, 0.02, 0.015, 0.1, 7], 7.8e-05], ['regression call spot discounting 2', ['C', 90.0, 100.0, 0.02, 0.015, 0.35, 7], 0.02433], ['partial repair probe 1', ['C', 100.0, 105.0, 0.02, 0.0, 0.2, 7], 0.04615], ['partial repair probe 2', ['C', 110.0, 105.0, 0.02, 0.0, 0.1, 182], 6.949255], ['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', 100.0, 100.0, 0.02, 0.015, 0.1, 0], 0.0], ['normal control 2', ['P', 110.0, 105.0, 0.05, 0.015, 0.2, 91], 1.934882]]]\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":"69bd2d500a054859024158f498bb72a772aa3e3a60e4cc7176ef150171cbc0f2","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 call spot discounting 1', ['C', 110.0, 105.0, 0.0, 0.015, 0.35, 91], 9.987818], ['regression call spot discounting 2', ['C', 110.0, 100.0, 0.02, 0.03, 0.2, 30], 10.017783], ['partial repair probe 1', ['C', 100.0, 105.0, 0.05, 0.0, 0.1, 730], 8.348306], ['partial repair probe 2', ['C', 100.0, 95.0, 0.02, 0.0, 0.1, 365], 8.228981], ['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', 100.0, 105.0, 0.0, 0.0, 0.2, 7], 5.044601], ['normal control 2', ['P', 110.0, 100.0, 0.02, 0.015, 0.2, 0], 0.0]], [['regression call spot discounting 1', ['C', 110.0, 105.0, 0.0, 0.015, 0.35, 7], 5.441716], ['regression call spot discounting 2', ['C', 110.0, 95.0, 0.0, 0.015, 0.1, 182], 14.246408], ['partial repair probe 1', ['C', 90.0, 100.0, 0.05, 0.0, 0.2, 7], 5.1e-05], ['partial repair probe 2', ['C', 90.0, 95.0, 0.02, 0.0, 0.35, 182], 7.16504], ['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, 100.0, 0.0, 0.03, 0.1, 1], 10.007397], ['normal control 2', ['P', 100.0, 100.0, 0.0, 0.0, 0.2, 1], 0.41763]], [['regression call spot discounting 1', ['C', 110.0, 105.0, 0.05, 0.015, 0.1, 91], 6.250733], ['regression call spot discounting 2', ['C', 110.0, 100.0, 0.0, 0.03, 0.35, 365], 17.981981], ['partial repair probe 1', ['C', 110.0, 95.0, 0.05, 0.0, 0.2, 730], 26.930371], ['partial repair probe 2', ['C', 110.0, 95.0, 0.05, 0.0, 0.1, 91], 16.177886], ['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', 110.0, 100.0, 0.05, 0.0, 0.1, 0], 0.0], ['normal control 2', ['P', 90.0, 95.0, 0.0, 0.0, 0.2, 0], 5.0]], [['regression call spot discounting 1', ['C', 90.0, 95.0, 0.02, 0.015, 0.1, 730], 3.308995], ['regression call spot discounting 2', ['C', 110.0, 95.0, 0.05, 0.03, 0.1, 730], 18.216377], ['partial repair probe 1', ['C', 90.0, 100.0, 0.05, 0.0, 0.35, 730], 17.398625], ['partial repair probe 2', ['C', 110.0, 105.0, 0.02, 0.0, 0.2, 365], 12.482761], ['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, 0.02, 0.0, 0.2, 0], 0.0], ['normal control 2', ['P', 110.0, 105.0, 0.02, 0.015, 0.1, 1], 0.0]], [['regression call spot discounting 1', ['C', 100.0, 105.0, 0.02, 0.015, 0.1, 7], 7.8e-05], ['regression call spot discounting 2', ['C', 90.0, 100.0, 0.02, 0.015, 0.35, 7], 0.02433], ['partial repair probe 1', ['C', 100.0, 105.0, 0.02, 0.0, 0.2, 7], 0.04615], ['partial repair probe 2', ['C', 110.0, 105.0, 0.02, 0.0, 0.1, 182], 6.949255], ['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', 100.0, 100.0, 0.02, 0.015, 0.1, 0], 0.0], ['normal control 2', ['P', 110.0, 105.0, 0.05, 0.015, 0.2, 91], 1.934882]]]\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-call-spot-discounting","generated_at":"2026-09-29T14:46:56.242394+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":"Discount the spot leg by e^{-qT}.","root_cause":"The call formula uses S*N(d1) without e^{-qT}.","sha256":"4bd75a0b2e682f39bded591cda5166a50fa0b9695b8fc6e2a6b5005d1fa71d25","title":"European option value with continuous dividend yield: the call leaves the spot term undiscounted for dividends · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":39.636,"exit_code":1,"observations":[{"actual":10.246547,"check":"regression call spot discounting 1","expected":9.987818,"passed":false},{"actual":10.103785,"check":"regression call spot discounting 2","expected":10.017783,"passed":false},{"actual":1.9969,"check":"partial repair probe 1","expected":8.348306,"passed":false},{"actual":6.689926,"check":"partial repair probe 2","expected":8.228981,"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":5.044601,"check":"normal control 1","expected":5.044601,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression call spot discounting 1\", \"actual\": 10.246547, \"expected\": 9.987818, \"passed\": false}, {\"check\": \"regression call spot discounting 2\", \"actual\": 10.103785, \"expected\": 10.017783, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 1.9969, \"expected\": 8.348306, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 6.689926, \"expected\": 8.228981, \"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\": 5.044601, \"expected\": 5.044601, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.46,"exit_code":1,"observations":[{"actual":10.246547,"check":"regression call spot discounting 1","expected":9.987818,"passed":false},{"actual":10.276,"check":"regression call spot discounting 2","expected":10.017783,"passed":false},{"actual":8.348306,"check":"partial repair probe 1","expected":8.348306,"passed":true},{"actual":8.228981,"check":"partial repair probe 2","expected":8.228981,"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":5.044601,"check":"normal control 1","expected":5.044601,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression call spot discounting 1\", \"actual\": 10.246547, \"expected\": 9.987818, \"passed\": false}, {\"check\": \"regression call spot discounting 2\", \"actual\": 10.276, \"expected\": 10.017783, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 8.348306, \"expected\": 8.348306, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 8.228981, \"expected\": 8.228981, \"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\": 5.044601, \"expected\": 5.044601, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":37.803,"exit_code":0,"observations":[{"actual":9.987818,"check":"regression call spot discounting 1","expected":9.987818,"passed":true},{"actual":10.017783,"check":"regression call spot discounting 2","expected":10.017783,"passed":true},{"actual":8.348306,"check":"partial repair probe 1","expected":8.348306,"passed":true},{"actual":8.228981,"check":"partial repair probe 2","expected":8.228981,"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":5.044601,"check":"normal control 1","expected":5.044601,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression call spot discounting 1\", \"actual\": 9.987818, \"expected\": 9.987818, \"passed\": true}, {\"check\": \"regression call spot discounting 2\", \"actual\": 10.017783, \"expected\": 10.017783, \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": 8.348306, \"expected\": 8.348306, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 8.228981, \"expected\": 8.228981, \"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\": 5.044601, \"expected\": 5.044601, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}