{"abstract":"Continuation values are biased toward the down state.","category":"Options payoff and settlement","checks":8,"contract":"Inputs kind, spot S, strike K, rate r, volatility sigma, maturity T in years and steps. dt=T/steps, u=exp(sigma*sqrt(dt)), d=1/u, p=(exp(r*dt)-d)/(u-d), disc=exp(-r*dt). Roll back from terminal payoffs; at each node take max(continuation, immediate exercise at that node's price). Return the root rounded to 6.","evaluation_group":"w2-options_payoff_and_settlement-crr-american","failed_approach":"Equal weights ignore the risk-neutral probability.","family":"w2-options_payoff_and_settlement-crr-american-continuation-weighting","id":"FA-61536","implementations":{"attempt":{"sha256":"5cb811a975debc4f7c9b30960b8738895d25bbf1ef4c702a03872b74bb4ba808","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(kind, S, K, r, sigma, T, steps):\n    dt = T / steps\n    u = math.exp(sigma * math.sqrt(dt))\n    d = 1 / u\n    p = (math.exp(r * dt) - d) / (u - d)\n    disc = math.exp(-r * dt)\n    def pay(s):\n        return max(s - K, 0.0) if kind == 'C' else max(K - s, 0.0)\n    vals = [pay(S * u ** j * d ** (steps - j)) for j in range(steps + 1)]\n    for i in range(steps - 1, -1, -1):\n        vals = [max(disc * 0.5 * (vals[j] + vals[j + 1]), pay(S * u ** j * d ** (i - j))) for j in range(i + 1)]\n    return round(vals[0], 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression continuation weighting 1', ['C', 95.0, 90.0, 0.0, 0.4, 0.5, 25], 13.005948], ['regression continuation weighting 2', ['C', 80.0, 105.0, 0.05, 0.25, 0.5, 12], 0.588112], ['partial repair probe 1', ['P', 80.0, 100.0, 0.01, 0.25, 2.0, 3], 23.588558], ['partial repair probe 2', ['C', 95.0, 100.0, 0.05, 0.4, 2.0, 25], 23.088626], ['normal control 1', ['P', 80.0, 105.0, 0.05, 0.25, 0.25, 12], 25.0], ['normal control 2', ['P', 110.0, 90.0, 0.05, 0.15, 0.25, 3], 0.0], ['normal control 3', ['P', 110.0, 90.0, 0.05, 0.15, 0.5, 3], 0.0], ['normal control 4', ['C', 80.0, 105.0, 0.08, 0.15, 0.25, 12], 0.0]], [['regression continuation weighting 1', ['P', 80.0, 100.0, 0.05, 0.4, 0.25, 5], 20.610754], ['regression continuation weighting 2', ['P', 110.0, 100.0, 0.05, 0.15, 1.0, 12], 1.445712], ['partial repair probe 1', ['C', 110.0, 90.0, 0.01, 0.25, 1.0, 12], 23.733528], ['partial repair probe 2', ['P', 100.0, 100.0, 0.05, 0.15, 0.5, 12], 3.26077], ['normal control 1', ['P', 80.0, 100.0, 0.01, 0.15, 0.5, 25], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.01, 0.15, 0.25, 25], 25.0], ['normal control 3', ['P', 80.0, 105.0, 0.08, 0.4, 0.25, 3], 25.0], ['normal control 4', ['P', 80.0, 105.0, 0.05, 0.25, 0.25, 3], 25.0]], [['regression continuation weighting 1', ['P', 110.0, 100.0, 0.01, 0.15, 0.5, 3], 1.063038], ['regression continuation weighting 2', ['P', 95.0, 105.0, 0.01, 0.25, 0.25, 25], 11.367995], ['partial repair probe 1', ['C', 80.0, 105.0, 0.08, 0.4, 0.25, 3], 0.995113], ['partial repair probe 2', ['P', 95.0, 105.0, 0.05, 0.15, 2.0, 5], 10.529554], ['normal control 1', ['P', 80.0, 100.0, 0.0, 0.15, 0.5, 3], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.05, 0.25, 0.5, 3], 25.0], ['normal control 3', ['P', 80.0, 105.0, 0.01, 0.15, 0.5, 3], 25.0], ['normal control 4', ['C', 80.0, 105.0, 0.05, 0.15, 0.25, 5], 0.0]], [['regression continuation weighting 1', ['P', 95.0, 105.0, 0.01, 0.15, 1.0, 25], 11.69818], ['regression continuation weighting 2', ['C', 95.0, 100.0, 0.01, 0.4, 1.0, 3], 14.601622], ['partial repair probe 1', ['P', 110.0, 90.0, 0.0, 0.25, 0.25, 5], 0.244718], ['partial repair probe 2', ['P', 110.0, 105.0, 0.08, 0.15, 1.0, 5], 2.188872], ['normal control 1', ['P', 80.0, 105.0, 0.01, 0.15, 1.0, 5], 25.0], ['normal control 2', ['C', 80.0, 105.0, 0.01, 0.15, 1.0, 3], 0.0], ['normal control 3', ['P', 80.0, 105.0, 0.0, 0.15, 1.0, 3], 25.0], ['normal control 4', ['P', 80.0, 105.0, 0.01, 0.15, 1.0, 12], 25.0]], [['regression continuation weighting 1', ['C', 110.0, 90.0, 0.0, 0.25, 1.0, 3], 22.873702], ['regression continuation weighting 2', ['P', 110.0, 100.0, 0.0, 0.25, 1.0, 5], 5.971362], ['partial repair probe 1', ['P', 80.0, 90.0, 0.05, 0.15, 2.0, 25], 10.363792], ['partial repair probe 2', ['P', 100.0, 90.0, 0.08, 0.4, 0.5, 25], 5.322102], ['normal control 1', ['P', 80.0, 100.0, 0.01, 0.15, 1.0, 5], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.0, 0.15, 1.0, 3], 25.0], ['normal control 3', ['P', 80.0, 100.0, 0.05, 0.25, 0.25, 3], 20.0], ['normal control 4', ['C', 80.0, 105.0, 0.08, 0.15, 0.25, 5], 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":"1a74248fad7aa3b4c60bc2302205e179153f7a1ee3adfe31e4282710232c03f0","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(kind, S, K, r, sigma, T, steps):\n    dt = T / steps\n    u = math.exp(sigma * math.sqrt(dt))\n    d = 1 / u\n    p = (math.exp(r * dt) - d) / (u - d)\n    disc = math.exp(-r * dt)\n    def pay(s):\n        return max(s - K, 0.0) if kind == 'C' else max(K - s, 0.0)\n    vals = [pay(S * u ** j * d ** (steps - j)) for j in range(steps + 1)]\n    for i in range(steps - 1, -1, -1):\n        vals = [max(disc * (p * vals[j] + (1 - p) * vals[j + 1]), pay(S * u ** j * d ** (i - j))) for j in range(i + 1)]\n    return round(vals[0], 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression continuation weighting 1', ['C', 95.0, 90.0, 0.0, 0.4, 0.5, 25], 13.005948], ['regression continuation weighting 2', ['C', 80.0, 105.0, 0.05, 0.25, 0.5, 12], 0.588112], ['partial repair probe 1', ['P', 80.0, 100.0, 0.01, 0.25, 2.0, 3], 23.588558], ['partial repair probe 2', ['C', 95.0, 100.0, 0.05, 0.4, 2.0, 25], 23.088626], ['normal control 1', ['P', 80.0, 105.0, 0.05, 0.25, 0.25, 12], 25.0], ['normal control 2', ['P', 110.0, 90.0, 0.05, 0.15, 0.25, 3], 0.0], ['normal control 3', ['P', 110.0, 90.0, 0.05, 0.15, 0.5, 3], 0.0], ['normal control 4', ['C', 80.0, 105.0, 0.08, 0.15, 0.25, 12], 0.0]], [['regression continuation weighting 1', ['P', 80.0, 100.0, 0.05, 0.4, 0.25, 5], 20.610754], ['regression continuation weighting 2', ['P', 110.0, 100.0, 0.05, 0.15, 1.0, 12], 1.445712], ['partial repair probe 1', ['C', 110.0, 90.0, 0.01, 0.25, 1.0, 12], 23.733528], ['partial repair probe 2', ['P', 100.0, 100.0, 0.05, 0.15, 0.5, 12], 3.26077], ['normal control 1', ['P', 80.0, 100.0, 0.01, 0.15, 0.5, 25], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.01, 0.15, 0.25, 25], 25.0], ['normal control 3', ['P', 80.0, 105.0, 0.08, 0.4, 0.25, 3], 25.0], ['normal control 4', ['P', 80.0, 105.0, 0.05, 0.25, 0.25, 3], 25.0]], [['regression continuation weighting 1', ['P', 110.0, 100.0, 0.01, 0.15, 0.5, 3], 1.063038], ['regression continuation weighting 2', ['P', 95.0, 105.0, 0.01, 0.25, 0.25, 25], 11.367995], ['partial repair probe 1', ['C', 80.0, 105.0, 0.08, 0.4, 0.25, 3], 0.995113], ['partial repair probe 2', ['P', 95.0, 105.0, 0.05, 0.15, 2.0, 5], 10.529554], ['normal control 1', ['P', 80.0, 100.0, 0.0, 0.15, 0.5, 3], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.05, 0.25, 0.5, 3], 25.0], ['normal control 3', ['P', 80.0, 105.0, 0.01, 0.15, 0.5, 3], 25.0], ['normal control 4', ['C', 80.0, 105.0, 0.05, 0.15, 0.25, 5], 0.0]], [['regression continuation weighting 1', ['P', 95.0, 105.0, 0.01, 0.15, 1.0, 25], 11.69818], ['regression continuation weighting 2', ['C', 95.0, 100.0, 0.01, 0.4, 1.0, 3], 14.601622], ['partial repair probe 1', ['P', 110.0, 90.0, 0.0, 0.25, 0.25, 5], 0.244718], ['partial repair probe 2', ['P', 110.0, 105.0, 0.08, 0.15, 1.0, 5], 2.188872], ['normal control 1', ['P', 80.0, 105.0, 0.01, 0.15, 1.0, 5], 25.0], ['normal control 2', ['C', 80.0, 105.0, 0.01, 0.15, 1.0, 3], 0.0], ['normal control 3', ['P', 80.0, 105.0, 0.0, 0.15, 1.0, 3], 25.0], ['normal control 4', ['P', 80.0, 105.0, 0.01, 0.15, 1.0, 12], 25.0]], [['regression continuation weighting 1', ['C', 110.0, 90.0, 0.0, 0.25, 1.0, 3], 22.873702], ['regression continuation weighting 2', ['P', 110.0, 100.0, 0.0, 0.25, 1.0, 5], 5.971362], ['partial repair probe 1', ['P', 80.0, 90.0, 0.05, 0.15, 2.0, 25], 10.363792], ['partial repair probe 2', ['P', 100.0, 90.0, 0.08, 0.4, 0.5, 25], 5.322102], ['normal control 1', ['P', 80.0, 100.0, 0.01, 0.15, 1.0, 5], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.0, 0.15, 1.0, 3], 25.0], ['normal control 3', ['P', 80.0, 100.0, 0.05, 0.25, 0.25, 3], 20.0], ['normal control 4', ['C', 80.0, 105.0, 0.08, 0.15, 0.25, 5], 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":"651d7b2bfb56cd0377ed6fac09770cb87a5c625e166b1d7a69f1af96b3eaecc1","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(kind, S, K, r, sigma, T, steps):\n    dt = T / steps\n    u = math.exp(sigma * math.sqrt(dt))\n    d = 1 / u\n    p = (math.exp(r * dt) - d) / (u - d)\n    disc = math.exp(-r * dt)\n    def pay(s):\n        return max(s - K, 0.0) if kind == 'C' else max(K - s, 0.0)\n    vals = [pay(S * u ** j * d ** (steps - j)) for j in range(steps + 1)]\n    for i in range(steps - 1, -1, -1):\n        vals = [max(disc * (p * vals[j + 1] + (1 - p) * vals[j]), pay(S * u ** j * d ** (i - j))) for j in range(i + 1)]\n    return round(vals[0], 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression continuation weighting 1', ['C', 95.0, 90.0, 0.0, 0.4, 0.5, 25], 13.005948], ['regression continuation weighting 2', ['C', 80.0, 105.0, 0.05, 0.25, 0.5, 12], 0.588112], ['partial repair probe 1', ['P', 80.0, 100.0, 0.01, 0.25, 2.0, 3], 23.588558], ['partial repair probe 2', ['C', 95.0, 100.0, 0.05, 0.4, 2.0, 25], 23.088626], ['normal control 1', ['P', 80.0, 105.0, 0.05, 0.25, 0.25, 12], 25.0], ['normal control 2', ['P', 110.0, 90.0, 0.05, 0.15, 0.25, 3], 0.0], ['normal control 3', ['P', 110.0, 90.0, 0.05, 0.15, 0.5, 3], 0.0], ['normal control 4', ['C', 80.0, 105.0, 0.08, 0.15, 0.25, 12], 0.0]], [['regression continuation weighting 1', ['P', 80.0, 100.0, 0.05, 0.4, 0.25, 5], 20.610754], ['regression continuation weighting 2', ['P', 110.0, 100.0, 0.05, 0.15, 1.0, 12], 1.445712], ['partial repair probe 1', ['C', 110.0, 90.0, 0.01, 0.25, 1.0, 12], 23.733528], ['partial repair probe 2', ['P', 100.0, 100.0, 0.05, 0.15, 0.5, 12], 3.26077], ['normal control 1', ['P', 80.0, 100.0, 0.01, 0.15, 0.5, 25], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.01, 0.15, 0.25, 25], 25.0], ['normal control 3', ['P', 80.0, 105.0, 0.08, 0.4, 0.25, 3], 25.0], ['normal control 4', ['P', 80.0, 105.0, 0.05, 0.25, 0.25, 3], 25.0]], [['regression continuation weighting 1', ['P', 110.0, 100.0, 0.01, 0.15, 0.5, 3], 1.063038], ['regression continuation weighting 2', ['P', 95.0, 105.0, 0.01, 0.25, 0.25, 25], 11.367995], ['partial repair probe 1', ['C', 80.0, 105.0, 0.08, 0.4, 0.25, 3], 0.995113], ['partial repair probe 2', ['P', 95.0, 105.0, 0.05, 0.15, 2.0, 5], 10.529554], ['normal control 1', ['P', 80.0, 100.0, 0.0, 0.15, 0.5, 3], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.05, 0.25, 0.5, 3], 25.0], ['normal control 3', ['P', 80.0, 105.0, 0.01, 0.15, 0.5, 3], 25.0], ['normal control 4', ['C', 80.0, 105.0, 0.05, 0.15, 0.25, 5], 0.0]], [['regression continuation weighting 1', ['P', 95.0, 105.0, 0.01, 0.15, 1.0, 25], 11.69818], ['regression continuation weighting 2', ['C', 95.0, 100.0, 0.01, 0.4, 1.0, 3], 14.601622], ['partial repair probe 1', ['P', 110.0, 90.0, 0.0, 0.25, 0.25, 5], 0.244718], ['partial repair probe 2', ['P', 110.0, 105.0, 0.08, 0.15, 1.0, 5], 2.188872], ['normal control 1', ['P', 80.0, 105.0, 0.01, 0.15, 1.0, 5], 25.0], ['normal control 2', ['C', 80.0, 105.0, 0.01, 0.15, 1.0, 3], 0.0], ['normal control 3', ['P', 80.0, 105.0, 0.0, 0.15, 1.0, 3], 25.0], ['normal control 4', ['P', 80.0, 105.0, 0.01, 0.15, 1.0, 12], 25.0]], [['regression continuation weighting 1', ['C', 110.0, 90.0, 0.0, 0.25, 1.0, 3], 22.873702], ['regression continuation weighting 2', ['P', 110.0, 100.0, 0.0, 0.25, 1.0, 5], 5.971362], ['partial repair probe 1', ['P', 80.0, 90.0, 0.05, 0.15, 2.0, 25], 10.363792], ['partial repair probe 2', ['P', 100.0, 90.0, 0.08, 0.4, 0.5, 25], 5.322102], ['normal control 1', ['P', 80.0, 100.0, 0.01, 0.15, 1.0, 5], 20.0], ['normal control 2', ['P', 80.0, 105.0, 0.0, 0.15, 1.0, 3], 25.0], ['normal control 3', ['P', 80.0, 100.0, 0.05, 0.25, 0.25, 3], 20.0], ['normal control 4', ['C', 80.0, 105.0, 0.08, 0.15, 0.25, 5], 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-crr-american-continuation-weighting","generated_at":"2026-09-29T14:46:56.133065+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":"Weight the up child vals[j+1] by p.","root_cause":"The continuation weights p on vals[j] and 1-p on vals[j+1].","sha256":"0427dc184e7139995633e17b2000cb3c159614feab1520af4aa006a5ba0a90f0","title":"Cox-Ross-Rubinstein American option tree: up and down probabilities are attached to the wrong children · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":39.318,"exit_code":1,"observations":[{"actual":15.552113,"check":"regression continuation weighting 1","expected":13.005948,"passed":false},{"actual":0.523556,"check":"regression continuation weighting 2","expected":0.588112,"passed":false},{"actual":22.434645,"check":"partial repair probe 1","expected":23.588558,"passed":false},{"actual":26.951753,"check":"partial repair probe 2","expected":23.088626,"passed":false},{"actual":25.0,"check":"normal control 1","expected":25.0,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true},{"actual":0.0,"check":"normal control 3","expected":0.0,"passed":true},{"actual":0.0,"check":"normal control 4","expected":0.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression continuation weighting 1\", \"actual\": 15.552113, \"expected\": 13.005948, \"passed\": false}, {\"check\": \"regression continuation weighting 2\", \"actual\": 0.523556, \"expected\": 0.588112, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 22.434645, \"expected\": 23.588558, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 26.951753, \"expected\": 23.088626, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": 25.0, \"expected\": 25.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.78,"exit_code":1,"observations":[{"actual":18.397987,"check":"regression continuation weighting 1","expected":13.005948,"passed":false},{"actual":0.465021,"check":"regression continuation weighting 2","expected":0.588112,"passed":false},{"actual":21.231316,"check":"partial repair probe 1","expected":23.588558,"passed":false},{"actual":31.269188,"check":"partial repair probe 2","expected":23.088626,"passed":false},{"actual":25.0,"check":"normal control 1","expected":25.0,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true},{"actual":0.0,"check":"normal control 3","expected":0.0,"passed":true},{"actual":0.0,"check":"normal control 4","expected":0.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression continuation weighting 1\", \"actual\": 18.397987, \"expected\": 13.005948, \"passed\": false}, {\"check\": \"regression continuation weighting 2\", \"actual\": 0.465021, \"expected\": 0.588112, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 21.231316, \"expected\": 23.588558, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 31.269188, \"expected\": 23.088626, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": 25.0, \"expected\": 25.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":38.18,"exit_code":0,"observations":[{"actual":13.005948,"check":"regression continuation weighting 1","expected":13.005948,"passed":true},{"actual":0.588112,"check":"regression continuation weighting 2","expected":0.588112,"passed":true},{"actual":23.588558,"check":"partial repair probe 1","expected":23.588558,"passed":true},{"actual":23.088626,"check":"partial repair probe 2","expected":23.088626,"passed":true},{"actual":25.0,"check":"normal control 1","expected":25.0,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true},{"actual":0.0,"check":"normal control 3","expected":0.0,"passed":true},{"actual":0.0,"check":"normal control 4","expected":0.0,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression continuation weighting 1\", \"actual\": 13.005948, \"expected\": 13.005948, \"passed\": true}, {\"check\": \"regression continuation weighting 2\", \"actual\": 0.588112, \"expected\": 0.588112, \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": 23.588558, \"expected\": 23.588558, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 23.088626, \"expected\": 23.088626, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 25.0, \"expected\": 25.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}