{"abstract":"Employees with additional withholding end up with odd-cent income tax despite electing whole dollars.","category":"Payroll withholding rules","checks":8,"contract":"Input {fit, extra, whole_dollar, fica}. Income tax withholding = fit + extra; when whole_dollar is elected, that sum is rounded to the nearest dollar (half-up). FICA is never rounded. Return [income_tax, income_tax + fica].","evaluation_group":"w2-payroll-withholding-whole-dollar-withholding","failed_approach":"The attempt skips rounding whenever extra withholding exists.","family":"w2-payroll-withholding-whole-dollar-withholding-extra-before-rounding","id":"FA-59331","implementations":{"attempt":{"sha256":"802eb1f272859cd6675d2c6107f8823dd4be00a395ce47da708b9663811e1595","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    fit = x['fit'] + x['extra']\n    if x['whole_dollar'] and x['extra'] == 0:\n        fit = (fit + 50) // 100 * 100\n    return [fit, fit + x['fica']]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'fit': 9156, 'extra': 2251, 'whole_dollar': True, 'fica': 25269}, [11400, 36669]), ('regression', {'fit': 8185, 'extra': 1110, 'whole_dollar': True, 'fica': 28304}, [9300, 37604]), ('partial-repair probe', {'fit': 90104, 'extra': 2500, 'whole_dollar': True, 'fica': 8194}, [92600, 100794]), ('partial-repair probe', {'fit': 132638, 'extra': 2500, 'whole_dollar': True, 'fica': 46802}, [135100, 181902]), ('normal control', {'fit': 69591, 'extra': 0, 'whole_dollar': False, 'fica': 14775}, [69591, 84366]), ('normal control', {'fit': 154831, 'extra': 3634, 'whole_dollar': False, 'fica': 44615}, [158465, 203080]), ('normal control', {'fit': 77351, 'extra': 0, 'whole_dollar': False, 'fica': 12610}, [77351, 89961]), ('normal control', {'fit': 88332, 'extra': 0, 'whole_dollar': True, 'fica': 8166}, [88300, 96466])], [('regression', {'fit': 8185, 'extra': 1110, 'whole_dollar': True, 'fica': 28304}, [9300, 37604]), ('regression', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('partial-repair probe', {'fit': 132638, 'extra': 2500, 'whole_dollar': True, 'fica': 46802}, [135100, 181902]), ('partial-repair probe', {'fit': 39742, 'extra': 2500, 'whole_dollar': True, 'fica': 2719}, [42200, 44919]), ('normal control', {'fit': 87258, 'extra': 0, 'whole_dollar': False, 'fica': 46798}, [87258, 134056]), ('normal control', {'fit': 118865, 'extra': 0, 'whole_dollar': False, 'fica': 28601}, [118865, 147466]), ('normal control', {'fit': 16677, 'extra': 0, 'whole_dollar': False, 'fica': 47905}, [16677, 64582]), ('normal control', {'fit': 72176, 'extra': 8810, 'whole_dollar': False, 'fica': 17211}, [80986, 98197])], [('regression', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('regression', {'fit': 71043, 'extra': 1719, 'whole_dollar': True, 'fica': 19074}, [72800, 91874]), ('partial-repair probe', {'fit': 39742, 'extra': 2500, 'whole_dollar': True, 'fica': 2719}, [42200, 44919]), ('partial-repair probe', {'fit': 46034, 'extra': 2500, 'whole_dollar': True, 'fica': 26997}, [48500, 75497]), ('normal control', {'fit': 53286, 'extra': 0, 'whole_dollar': False, 'fica': 40551}, [53286, 93837]), ('normal control', {'fit': 76409, 'extra': 0, 'whole_dollar': False, 'fica': 47429}, [76409, 123838]), ('normal control', {'fit': 158877, 'extra': 0, 'whole_dollar': False, 'fica': 16786}, [158877, 175663]), ('normal control', {'fit': 83141, 'extra': 0, 'whole_dollar': True, 'fica': 11931}, [83100, 95031])], [('regression', {'fit': 71043, 'extra': 1719, 'whole_dollar': True, 'fica': 19074}, [72800, 91874]), ('regression', {'fit': 187550, 'extra': 8476, 'whole_dollar': True, 'fica': 45605}, [196000, 241605]), ('partial-repair probe', {'fit': 160110, 'extra': 2500, 'whole_dollar': True, 'fica': 47818}, [162600, 210418]), ('partial-repair probe', {'fit': 117866, 'extra': 2500, 'whole_dollar': True, 'fica': 44243}, [120400, 164643]), ('normal control', {'fit': 77435, 'extra': 0, 'whole_dollar': True, 'fica': 39916}, [77400, 117316]), ('normal control', {'fit': 16947, 'extra': 0, 'whole_dollar': True, 'fica': 9583}, [16900, 26483]), ('normal control', {'fit': 45654, 'extra': 0, 'whole_dollar': True, 'fica': 24238}, [45700, 69938]), ('normal control', {'fit': 69043, 'extra': 0, 'whole_dollar': True, 'fica': 38706}, [69000, 107706])], [('regression', {'fit': 187550, 'extra': 8476, 'whole_dollar': True, 'fica': 45605}, [196000, 241605]), ('regression', {'fit': 144230, 'extra': 9285, 'whole_dollar': True, 'fica': 21550}, [153500, 175050]), ('partial-repair probe', {'fit': 151775, 'extra': 2500, 'whole_dollar': True, 'fica': 42505}, [154300, 196805]), ('partial-repair probe', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('normal control', {'fit': 12373, 'extra': 1118, 'whole_dollar': False, 'fica': 16260}, [13491, 29751]), ('normal control', {'fit': 31187, 'extra': 0, 'whole_dollar': False, 'fica': 13316}, [31187, 44503]), ('normal control', {'fit': 15705, 'extra': 0, 'whole_dollar': True, 'fica': 2352}, [15700, 18052]), ('normal control', {'fit': 91543, 'extra': 0, 'whole_dollar': True, 'fica': 21661}, [91500, 113161])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), 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":"ad42a7855da54dc02f872b25589941021dc59d1c9bd3826c4326a3a213f993ea","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    fit = x['fit']\n    if x['whole_dollar']:\n        fit = (fit + 50) // 100 * 100\n    fit += x['extra']\n    return [fit, fit + x['fica']]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'fit': 9156, 'extra': 2251, 'whole_dollar': True, 'fica': 25269}, [11400, 36669]), ('regression', {'fit': 8185, 'extra': 1110, 'whole_dollar': True, 'fica': 28304}, [9300, 37604]), ('partial-repair probe', {'fit': 90104, 'extra': 2500, 'whole_dollar': True, 'fica': 8194}, [92600, 100794]), ('partial-repair probe', {'fit': 132638, 'extra': 2500, 'whole_dollar': True, 'fica': 46802}, [135100, 181902]), ('normal control', {'fit': 69591, 'extra': 0, 'whole_dollar': False, 'fica': 14775}, [69591, 84366]), ('normal control', {'fit': 154831, 'extra': 3634, 'whole_dollar': False, 'fica': 44615}, [158465, 203080]), ('normal control', {'fit': 77351, 'extra': 0, 'whole_dollar': False, 'fica': 12610}, [77351, 89961]), ('normal control', {'fit': 88332, 'extra': 0, 'whole_dollar': True, 'fica': 8166}, [88300, 96466])], [('regression', {'fit': 8185, 'extra': 1110, 'whole_dollar': True, 'fica': 28304}, [9300, 37604]), ('regression', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('partial-repair probe', {'fit': 132638, 'extra': 2500, 'whole_dollar': True, 'fica': 46802}, [135100, 181902]), ('partial-repair probe', {'fit': 39742, 'extra': 2500, 'whole_dollar': True, 'fica': 2719}, [42200, 44919]), ('normal control', {'fit': 87258, 'extra': 0, 'whole_dollar': False, 'fica': 46798}, [87258, 134056]), ('normal control', {'fit': 118865, 'extra': 0, 'whole_dollar': False, 'fica': 28601}, [118865, 147466]), ('normal control', {'fit': 16677, 'extra': 0, 'whole_dollar': False, 'fica': 47905}, [16677, 64582]), ('normal control', {'fit': 72176, 'extra': 8810, 'whole_dollar': False, 'fica': 17211}, [80986, 98197])], [('regression', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('regression', {'fit': 71043, 'extra': 1719, 'whole_dollar': True, 'fica': 19074}, [72800, 91874]), ('partial-repair probe', {'fit': 39742, 'extra': 2500, 'whole_dollar': True, 'fica': 2719}, [42200, 44919]), ('partial-repair probe', {'fit': 46034, 'extra': 2500, 'whole_dollar': True, 'fica': 26997}, [48500, 75497]), ('normal control', {'fit': 53286, 'extra': 0, 'whole_dollar': False, 'fica': 40551}, [53286, 93837]), ('normal control', {'fit': 76409, 'extra': 0, 'whole_dollar': False, 'fica': 47429}, [76409, 123838]), ('normal control', {'fit': 158877, 'extra': 0, 'whole_dollar': False, 'fica': 16786}, [158877, 175663]), ('normal control', {'fit': 83141, 'extra': 0, 'whole_dollar': True, 'fica': 11931}, [83100, 95031])], [('regression', {'fit': 71043, 'extra': 1719, 'whole_dollar': True, 'fica': 19074}, [72800, 91874]), ('regression', {'fit': 187550, 'extra': 8476, 'whole_dollar': True, 'fica': 45605}, [196000, 241605]), ('partial-repair probe', {'fit': 160110, 'extra': 2500, 'whole_dollar': True, 'fica': 47818}, [162600, 210418]), ('partial-repair probe', {'fit': 117866, 'extra': 2500, 'whole_dollar': True, 'fica': 44243}, [120400, 164643]), ('normal control', {'fit': 77435, 'extra': 0, 'whole_dollar': True, 'fica': 39916}, [77400, 117316]), ('normal control', {'fit': 16947, 'extra': 0, 'whole_dollar': True, 'fica': 9583}, [16900, 26483]), ('normal control', {'fit': 45654, 'extra': 0, 'whole_dollar': True, 'fica': 24238}, [45700, 69938]), ('normal control', {'fit': 69043, 'extra': 0, 'whole_dollar': True, 'fica': 38706}, [69000, 107706])], [('regression', {'fit': 187550, 'extra': 8476, 'whole_dollar': True, 'fica': 45605}, [196000, 241605]), ('regression', {'fit': 144230, 'extra': 9285, 'whole_dollar': True, 'fica': 21550}, [153500, 175050]), ('partial-repair probe', {'fit': 151775, 'extra': 2500, 'whole_dollar': True, 'fica': 42505}, [154300, 196805]), ('partial-repair probe', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('normal control', {'fit': 12373, 'extra': 1118, 'whole_dollar': False, 'fica': 16260}, [13491, 29751]), ('normal control', {'fit': 31187, 'extra': 0, 'whole_dollar': False, 'fica': 13316}, [31187, 44503]), ('normal control', {'fit': 15705, 'extra': 0, 'whole_dollar': True, 'fica': 2352}, [15700, 18052]), ('normal control', {'fit': 91543, 'extra': 0, 'whole_dollar': True, 'fica': 21661}, [91500, 113161])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), 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":"dca66c581d80a18a558e2f8dba1ed973aae49cc7e41baf5838e37db37be315fa","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    fit = x['fit'] + x['extra']\n    if x['whole_dollar']:\n        fit = (fit + 50) // 100 * 100\n    return [fit, fit + x['fica']]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'fit': 9156, 'extra': 2251, 'whole_dollar': True, 'fica': 25269}, [11400, 36669]), ('regression', {'fit': 8185, 'extra': 1110, 'whole_dollar': True, 'fica': 28304}, [9300, 37604]), ('partial-repair probe', {'fit': 90104, 'extra': 2500, 'whole_dollar': True, 'fica': 8194}, [92600, 100794]), ('partial-repair probe', {'fit': 132638, 'extra': 2500, 'whole_dollar': True, 'fica': 46802}, [135100, 181902]), ('normal control', {'fit': 69591, 'extra': 0, 'whole_dollar': False, 'fica': 14775}, [69591, 84366]), ('normal control', {'fit': 154831, 'extra': 3634, 'whole_dollar': False, 'fica': 44615}, [158465, 203080]), ('normal control', {'fit': 77351, 'extra': 0, 'whole_dollar': False, 'fica': 12610}, [77351, 89961]), ('normal control', {'fit': 88332, 'extra': 0, 'whole_dollar': True, 'fica': 8166}, [88300, 96466])], [('regression', {'fit': 8185, 'extra': 1110, 'whole_dollar': True, 'fica': 28304}, [9300, 37604]), ('regression', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('partial-repair probe', {'fit': 132638, 'extra': 2500, 'whole_dollar': True, 'fica': 46802}, [135100, 181902]), ('partial-repair probe', {'fit': 39742, 'extra': 2500, 'whole_dollar': True, 'fica': 2719}, [42200, 44919]), ('normal control', {'fit': 87258, 'extra': 0, 'whole_dollar': False, 'fica': 46798}, [87258, 134056]), ('normal control', {'fit': 118865, 'extra': 0, 'whole_dollar': False, 'fica': 28601}, [118865, 147466]), ('normal control', {'fit': 16677, 'extra': 0, 'whole_dollar': False, 'fica': 47905}, [16677, 64582]), ('normal control', {'fit': 72176, 'extra': 8810, 'whole_dollar': False, 'fica': 17211}, [80986, 98197])], [('regression', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('regression', {'fit': 71043, 'extra': 1719, 'whole_dollar': True, 'fica': 19074}, [72800, 91874]), ('partial-repair probe', {'fit': 39742, 'extra': 2500, 'whole_dollar': True, 'fica': 2719}, [42200, 44919]), ('partial-repair probe', {'fit': 46034, 'extra': 2500, 'whole_dollar': True, 'fica': 26997}, [48500, 75497]), ('normal control', {'fit': 53286, 'extra': 0, 'whole_dollar': False, 'fica': 40551}, [53286, 93837]), ('normal control', {'fit': 76409, 'extra': 0, 'whole_dollar': False, 'fica': 47429}, [76409, 123838]), ('normal control', {'fit': 158877, 'extra': 0, 'whole_dollar': False, 'fica': 16786}, [158877, 175663]), ('normal control', {'fit': 83141, 'extra': 0, 'whole_dollar': True, 'fica': 11931}, [83100, 95031])], [('regression', {'fit': 71043, 'extra': 1719, 'whole_dollar': True, 'fica': 19074}, [72800, 91874]), ('regression', {'fit': 187550, 'extra': 8476, 'whole_dollar': True, 'fica': 45605}, [196000, 241605]), ('partial-repair probe', {'fit': 160110, 'extra': 2500, 'whole_dollar': True, 'fica': 47818}, [162600, 210418]), ('partial-repair probe', {'fit': 117866, 'extra': 2500, 'whole_dollar': True, 'fica': 44243}, [120400, 164643]), ('normal control', {'fit': 77435, 'extra': 0, 'whole_dollar': True, 'fica': 39916}, [77400, 117316]), ('normal control', {'fit': 16947, 'extra': 0, 'whole_dollar': True, 'fica': 9583}, [16900, 26483]), ('normal control', {'fit': 45654, 'extra': 0, 'whole_dollar': True, 'fica': 24238}, [45700, 69938]), ('normal control', {'fit': 69043, 'extra': 0, 'whole_dollar': True, 'fica': 38706}, [69000, 107706])], [('regression', {'fit': 187550, 'extra': 8476, 'whole_dollar': True, 'fica': 45605}, [196000, 241605]), ('regression', {'fit': 144230, 'extra': 9285, 'whole_dollar': True, 'fica': 21550}, [153500, 175050]), ('partial-repair probe', {'fit': 151775, 'extra': 2500, 'whole_dollar': True, 'fica': 42505}, [154300, 196805]), ('partial-repair probe', {'fit': 15510, 'extra': 5992, 'whole_dollar': True, 'fica': 2377}, [21500, 23877]), ('normal control', {'fit': 12373, 'extra': 1118, 'whole_dollar': False, 'fica': 16260}, [13491, 29751]), ('normal control', {'fit': 31187, 'extra': 0, 'whole_dollar': False, 'fica': 13316}, [31187, 44503]), ('normal control', {'fit': 15705, 'extra': 0, 'whole_dollar': True, 'fica': 2352}, [15700, 18052]), ('normal control', {'fit': 91543, 'extra': 0, 'whole_dollar': True, 'fica': 21661}, [91500, 113161])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), 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 teaching model of a stipulated payroll rule with toy thresholds and rates. It makes no claim of conformance to any tax authority, statute or jurisdiction and is not payroll software. 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-payroll-withholding-whole-dollar-withholding-extra-before-rounding","generated_at":"2026-09-29T14:46:35.234706+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Whole-dollar rounding is optional for income tax only and must be applied after all income tax components.","repair":"Restore the contract rule at the extra before rounding step: use `fit = x['fit'] + x['extra']\nif x['whole_dollar']:\n    fit = (fit + 50) // 100 * 100`.","root_cause":"Extra withholding is added after rounding instead of being included in the rounded amount.","sha256":"957421ef0482db6e19431e7d5f4efabef3e61beb73d066435cf0387e747d2c19","title":"Whole-dollar income tax withholding option: extra before rounding · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":42.379,"exit_code":1,"observations":[{"actual":[11407,36676],"check":"regression 0","expected":[11400,36669],"passed":false},{"actual":[9295,37599],"check":"regression 1","expected":[9300,37604],"passed":false},{"actual":[92604,100798],"check":"partial-repair probe 2","expected":[92600,100794],"passed":false},{"actual":[135138,181940],"check":"partial-repair probe 3","expected":[135100,181902],"passed":false},{"actual":[69591,84366],"check":"normal control 4","expected":[69591,84366],"passed":true},{"actual":[158465,203080],"check":"normal control 5","expected":[158465,203080],"passed":true},{"actual":[77351,89961],"check":"normal control 6","expected":[77351,89961],"passed":true},{"actual":[88300,96466],"check":"normal control 7","expected":[88300,96466],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [11407, 36676], \"expected\": [11400, 36669], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [9295, 37599], \"expected\": [9300, 37604], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [92604, 100798], \"expected\": [92600, 100794], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [135138, 181940], \"expected\": [135100, 181902], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [69591, 84366], \"expected\": [69591, 84366], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [158465, 203080], \"expected\": [158465, 203080], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [77351, 89961], \"expected\": [77351, 89961], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [88300, 96466], \"expected\": [88300, 96466], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.554,"exit_code":1,"observations":[{"actual":[11451,36720],"check":"regression 0","expected":[11400,36669],"passed":false},{"actual":[9310,37614],"check":"regression 1","expected":[9300,37604],"passed":false},{"actual":[92600,100794],"check":"partial-repair probe 2","expected":[92600,100794],"passed":true},{"actual":[135100,181902],"check":"partial-repair probe 3","expected":[135100,181902],"passed":true},{"actual":[69591,84366],"check":"normal control 4","expected":[69591,84366],"passed":true},{"actual":[158465,203080],"check":"normal control 5","expected":[158465,203080],"passed":true},{"actual":[77351,89961],"check":"normal control 6","expected":[77351,89961],"passed":true},{"actual":[88300,96466],"check":"normal control 7","expected":[88300,96466],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [11451, 36720], \"expected\": [11400, 36669], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [9310, 37614], \"expected\": [9300, 37604], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [92600, 100794], \"expected\": [92600, 100794], \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": [135100, 181902], \"expected\": [135100, 181902], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [69591, 84366], \"expected\": [69591, 84366], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [158465, 203080], \"expected\": [158465, 203080], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [77351, 89961], \"expected\": [77351, 89961], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [88300, 96466], \"expected\": [88300, 96466], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":41.601,"exit_code":0,"observations":[{"actual":[11400,36669],"check":"regression 0","expected":[11400,36669],"passed":true},{"actual":[9300,37604],"check":"regression 1","expected":[9300,37604],"passed":true},{"actual":[92600,100794],"check":"partial-repair probe 2","expected":[92600,100794],"passed":true},{"actual":[135100,181902],"check":"partial-repair probe 3","expected":[135100,181902],"passed":true},{"actual":[69591,84366],"check":"normal control 4","expected":[69591,84366],"passed":true},{"actual":[158465,203080],"check":"normal control 5","expected":[158465,203080],"passed":true},{"actual":[77351,89961],"check":"normal control 6","expected":[77351,89961],"passed":true},{"actual":[88300,96466],"check":"normal control 7","expected":[88300,96466],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [11400, 36669], \"expected\": [11400, 36669], \"passed\": true}, {\"check\": \"regression 1\", \"actual\": [9300, 37604], \"expected\": [9300, 37604], \"passed\": true}, {\"check\": \"partial-repair probe 2\", \"actual\": [92600, 100794], \"expected\": [92600, 100794], \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": [135100, 181902], \"expected\": [135100, 181902], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [69591, 84366], \"expected\": [69591, 84366], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [158465, 203080], \"expected\": [158465, 203080], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [77351, 89961], \"expected\": [77351, 89961], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [88300, 96466], \"expected\": [88300, 96466], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}