{"abstract":"After a two-way tie for first, the next player still receives 2 bonus.","category":"Fantasy sports scoring","checks":7,"contract":"Allocate bonus points from a per-match performance index: rank players by index descending; positions 1, 2, 3 earn 3, 2, 1. Tied players all receive the award of the first position their group occupies and consume as many positions as the group size, so a two-way tie for first earns 3 each and the next player 1. Players whose index is 0 or below never receive bonus. Return name -> bonus for awarded players.","evaluation_group":"w2-fantasy-sports-scoring-bonus-point-ranks","failed_approach":"Resetting the position to the group size forgets positions consumed earlier.","family":"w2-fantasy-sports-scoring-bonus-point-ranks-position-consumption","id":"FA-85266","implementations":{"attempt":{"sha256":"1aaa9c351c7b0607d04feb1285f18e5ab0909a908508d9dd8d790d137b6f2265","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(bps):\n    ordered = sorted(bps.items(), key=lambda kv: (-kv[1], kv[0]))\n    award = [3, 2, 1]\n    out = {}\n    pos = 0\n    i = 0\n    while i < len(ordered) and pos < 3:\n        j = i\n        while j < len(ordered) and ordered[j][1] == ordered[i][1]:\n            j += 1\n        for name, v in ordered[i:j]:\n            if v > 0:\n                out[name] = award[pos]\n        pos = j - i\n        i = j\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: position consumption', [{'bo': 34, 'ce': 12, 'ek': 4, 'fu': 34}],\n   {'bo': 3, 'ce': 1, 'fu': 3}),\n  ('partial repair probe: position consumption',\n   [{'ax': 30, 'bo': -2, 'ce': 27, 'di': 32, 'ek': 27, 'fu': 12, 'gi': 34, 'ho': 30}],\n   {'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}),\n  ('second regression', [{'ax': 0, 'ce': 34, 'di': -2, 'ek': 5, 'fu': 12, 'gi': 27}],\n   {'ce': 3, 'fu': 1, 'gi': 2}),\n  ('normal control 1', [{'bo': 30, 'ek': 30, 'fu': 34, 'gi': 0, 'ho': -2}], {'bo': 2, 'ek': 2, 'fu': 3}),\n  ('normal control 2', [{'ce': 0, 'di': 30, 'ek': 34}], {'di': 2, 'ek': 3}),\n  ('normal control 3', [{'ce': 30, 'di': -2, 'fu': -2, 'gi': 0}], {'ce': 3}),\n  ('normal control 4', [{'ax': 30, 'bo': -2, 'ce': 30, 'ek': 30}], {'ax': 3, 'ce': 3, 'ek': 3})],\n [('regression: position consumption', [{'ax': 34, 'bo': 30, 'fu': -2, 'gi': 34, 'ho': 0}],\n   {'ax': 3, 'bo': 1, 'gi': 3}),\n  ('partial repair probe: position consumption', [{'bo': 34, 'ce': 34, 'ek': 30, 'fu': 26}],\n   {'bo': 3, 'ce': 3, 'ek': 1}),\n  ('second regression', [{'ax': 34, 'ce': 7, 'di': 0, 'gi': 34}], {'ax': 3, 'ce': 1, 'gi': 3}),\n  ('normal control 1', [{'ce': 0, 'gi': -2, 'ho': -2}], {}),\n  ('normal control 2', [{'ce': 12, 'ek': -2, 'fu': 29, 'ho': 12}], {'ce': 2, 'fu': 3, 'ho': 2}),\n  ('normal control 3', [{'ce': -2, 'ek': 34, 'fu': 12}], {'ek': 3, 'fu': 2}),\n  ('normal control 4', [{'ce': 34, 'di': -2, 'gi': 30}], {'ce': 3, 'gi': 2})],\n [('regression: position consumption', [{'ax': 34, 'bo': 12, 'ce': 34, 'di': 34, 'fu': 0, 'gi': 30, 'ho': 0}],\n   {'ax': 3, 'ce': 3, 'di': 3}),\n  ('partial repair probe: position consumption', [{'bo': 0, 'ce': 17, 'fu': 30, 'ho': 34}],\n   {'ce': 1, 'fu': 2, 'ho': 3}),\n  ('second regression', [{'ax': 34, 'ek': 28, 'gi': 30}], {'ax': 3, 'ek': 1, 'gi': 2}),\n  ('normal control 1', [{'ce': 34, 'di': 0, 'ek': 34}], {'ce': 3, 'ek': 3}),\n  ('normal control 2', [{'bo': -2, 'di': -2, 'fu': 24}], {'fu': 3}),\n  ('normal control 3', [{'ax': 0, 'di': 0, 'fu': 30, 'ho': 12}], {'fu': 3, 'ho': 2}),\n  ('normal control 4', [{'ax': 34, 'bo': -2, 'ce': -2, 'ek': 0, 'fu': 12, 'gi': 0, 'ho': -2}],\n   {'ax': 3, 'fu': 2})],\n [('regression: position consumption',\n   [{'ax': 12, 'bo': 34, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 12, 'gi': 34, 'ho': 27}],\n   {'bo': 3, 'ce': 3, 'gi': 3}),\n  ('partial repair probe: position consumption', [{'ax': 12, 'ce': 30, 'ek': 27, 'ho': -2}],\n   {'ax': 1, 'ce': 3, 'ek': 2}),\n  ('second regression', [{'ax': 27, 'bo': 0, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 27, 'gi': 30, 'ho': 0}],\n   {'ax': 1, 'ce': 3, 'fu': 1, 'gi': 2}),\n  ('normal control 1', [{'bo': 12, 'di': 34, 'fu': 0}], {'bo': 2, 'di': 3}),\n  ('normal control 2', [{'ax': 0, 'ce': 0, 'fu': -2}], {}),\n  ('normal control 3', [{'ax': 30, 'ek': 30, 'gi': 34}], {'ax': 2, 'ek': 2, 'gi': 3}),\n  ('normal control 4', [{'ce': -2, 'di': 0, 'fu': 34, 'ho': 34}], {'fu': 3, 'ho': 3})],\n [('regression: position consumption',\n   [{'ax': 12, 'bo': 34, 'ce': 0, 'di': 34, 'fu': 30, 'gi': 34, 'ho': 30}], {'bo': 3, 'di': 3, 'gi': 3}),\n  ('partial repair probe: position consumption',\n   [{'ax': 30, 'bo': 0, 'ce': 0, 'ek': 27, 'fu': 27, 'gi': 12, 'ho': 34}],\n   {'ax': 2, 'ek': 1, 'fu': 1, 'ho': 3}),\n  ('second regression', [{'ax': 27, 'ce': 8, 'di': 0, 'fu': 30, 'gi': -2}], {'ax': 2, 'ce': 1, 'fu': 3}),\n  ('normal control 1', [{'bo': 34, 'di': 27, 'ek': -2}], {'bo': 3, 'di': 2}),\n  ('normal control 2', [{'ax': 30, 'bo': 12, 'ce': 0, 'fu': 12, 'ho': 12}],\n   {'ax': 3, 'bo': 2, 'fu': 2, 'ho': 2}),\n  ('normal control 3', [{'ax': -2, 'ce': -2, 'di': -2, 'ek': -2}], {}),\n  ('normal control 4', [{'bo': -2, 'gi': 0, 'ho': 12}], {'ho': 3})]]\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":"0818f403ff348a89ee2d4d69068d5f8ff1f09a1d17f2d0b59d49695f60d943e6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(bps):\n    ordered = sorted(bps.items(), key=lambda kv: (-kv[1], kv[0]))\n    award = [3, 2, 1]\n    out = {}\n    pos = 0\n    i = 0\n    while i < len(ordered) and pos < 3:\n        j = i\n        while j < len(ordered) and ordered[j][1] == ordered[i][1]:\n            j += 1\n        for name, v in ordered[i:j]:\n            if v > 0:\n                out[name] = award[pos]\n        pos += 1\n        i = j\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: position consumption', [{'bo': 34, 'ce': 12, 'ek': 4, 'fu': 34}],\n   {'bo': 3, 'ce': 1, 'fu': 3}),\n  ('partial repair probe: position consumption',\n   [{'ax': 30, 'bo': -2, 'ce': 27, 'di': 32, 'ek': 27, 'fu': 12, 'gi': 34, 'ho': 30}],\n   {'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}),\n  ('second regression', [{'ax': 0, 'ce': 34, 'di': -2, 'ek': 5, 'fu': 12, 'gi': 27}],\n   {'ce': 3, 'fu': 1, 'gi': 2}),\n  ('normal control 1', [{'bo': 30, 'ek': 30, 'fu': 34, 'gi': 0, 'ho': -2}], {'bo': 2, 'ek': 2, 'fu': 3}),\n  ('normal control 2', [{'ce': 0, 'di': 30, 'ek': 34}], {'di': 2, 'ek': 3}),\n  ('normal control 3', [{'ce': 30, 'di': -2, 'fu': -2, 'gi': 0}], {'ce': 3}),\n  ('normal control 4', [{'ax': 30, 'bo': -2, 'ce': 30, 'ek': 30}], {'ax': 3, 'ce': 3, 'ek': 3})],\n [('regression: position consumption', [{'ax': 34, 'bo': 30, 'fu': -2, 'gi': 34, 'ho': 0}],\n   {'ax': 3, 'bo': 1, 'gi': 3}),\n  ('partial repair probe: position consumption', [{'bo': 34, 'ce': 34, 'ek': 30, 'fu': 26}],\n   {'bo': 3, 'ce': 3, 'ek': 1}),\n  ('second regression', [{'ax': 34, 'ce': 7, 'di': 0, 'gi': 34}], {'ax': 3, 'ce': 1, 'gi': 3}),\n  ('normal control 1', [{'ce': 0, 'gi': -2, 'ho': -2}], {}),\n  ('normal control 2', [{'ce': 12, 'ek': -2, 'fu': 29, 'ho': 12}], {'ce': 2, 'fu': 3, 'ho': 2}),\n  ('normal control 3', [{'ce': -2, 'ek': 34, 'fu': 12}], {'ek': 3, 'fu': 2}),\n  ('normal control 4', [{'ce': 34, 'di': -2, 'gi': 30}], {'ce': 3, 'gi': 2})],\n [('regression: position consumption', [{'ax': 34, 'bo': 12, 'ce': 34, 'di': 34, 'fu': 0, 'gi': 30, 'ho': 0}],\n   {'ax': 3, 'ce': 3, 'di': 3}),\n  ('partial repair probe: position consumption', [{'bo': 0, 'ce': 17, 'fu': 30, 'ho': 34}],\n   {'ce': 1, 'fu': 2, 'ho': 3}),\n  ('second regression', [{'ax': 34, 'ek': 28, 'gi': 30}], {'ax': 3, 'ek': 1, 'gi': 2}),\n  ('normal control 1', [{'ce': 34, 'di': 0, 'ek': 34}], {'ce': 3, 'ek': 3}),\n  ('normal control 2', [{'bo': -2, 'di': -2, 'fu': 24}], {'fu': 3}),\n  ('normal control 3', [{'ax': 0, 'di': 0, 'fu': 30, 'ho': 12}], {'fu': 3, 'ho': 2}),\n  ('normal control 4', [{'ax': 34, 'bo': -2, 'ce': -2, 'ek': 0, 'fu': 12, 'gi': 0, 'ho': -2}],\n   {'ax': 3, 'fu': 2})],\n [('regression: position consumption',\n   [{'ax': 12, 'bo': 34, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 12, 'gi': 34, 'ho': 27}],\n   {'bo': 3, 'ce': 3, 'gi': 3}),\n  ('partial repair probe: position consumption', [{'ax': 12, 'ce': 30, 'ek': 27, 'ho': -2}],\n   {'ax': 1, 'ce': 3, 'ek': 2}),\n  ('second regression', [{'ax': 27, 'bo': 0, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 27, 'gi': 30, 'ho': 0}],\n   {'ax': 1, 'ce': 3, 'fu': 1, 'gi': 2}),\n  ('normal control 1', [{'bo': 12, 'di': 34, 'fu': 0}], {'bo': 2, 'di': 3}),\n  ('normal control 2', [{'ax': 0, 'ce': 0, 'fu': -2}], {}),\n  ('normal control 3', [{'ax': 30, 'ek': 30, 'gi': 34}], {'ax': 2, 'ek': 2, 'gi': 3}),\n  ('normal control 4', [{'ce': -2, 'di': 0, 'fu': 34, 'ho': 34}], {'fu': 3, 'ho': 3})],\n [('regression: position consumption',\n   [{'ax': 12, 'bo': 34, 'ce': 0, 'di': 34, 'fu': 30, 'gi': 34, 'ho': 30}], {'bo': 3, 'di': 3, 'gi': 3}),\n  ('partial repair probe: position consumption',\n   [{'ax': 30, 'bo': 0, 'ce': 0, 'ek': 27, 'fu': 27, 'gi': 12, 'ho': 34}],\n   {'ax': 2, 'ek': 1, 'fu': 1, 'ho': 3}),\n  ('second regression', [{'ax': 27, 'ce': 8, 'di': 0, 'fu': 30, 'gi': -2}], {'ax': 2, 'ce': 1, 'fu': 3}),\n  ('normal control 1', [{'bo': 34, 'di': 27, 'ek': -2}], {'bo': 3, 'di': 2}),\n  ('normal control 2', [{'ax': 30, 'bo': 12, 'ce': 0, 'fu': 12, 'ho': 12}],\n   {'ax': 3, 'bo': 2, 'fu': 2, 'ho': 2}),\n  ('normal control 3', [{'ax': -2, 'ce': -2, 'di': -2, 'ek': -2}], {}),\n  ('normal control 4', [{'bo': -2, 'gi': 0, 'ho': 12}], {'ho': 3})]]\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":"cd16106aa831cd64a22ecb670e6fdaca6d9cd005db054bb117f147a044d8cd6f","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(bps):\n    ordered = sorted(bps.items(), key=lambda kv: (-kv[1], kv[0]))\n    award = [3, 2, 1]\n    out = {}\n    pos = 0\n    i = 0\n    while i < len(ordered) and pos < 3:\n        j = i\n        while j < len(ordered) and ordered[j][1] == ordered[i][1]:\n            j += 1\n        for name, v in ordered[i:j]:\n            if v > 0:\n                out[name] = award[pos]\n        pos += j - i\n        i = j\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: position consumption', [{'bo': 34, 'ce': 12, 'ek': 4, 'fu': 34}],\n   {'bo': 3, 'ce': 1, 'fu': 3}),\n  ('partial repair probe: position consumption',\n   [{'ax': 30, 'bo': -2, 'ce': 27, 'di': 32, 'ek': 27, 'fu': 12, 'gi': 34, 'ho': 30}],\n   {'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}),\n  ('second regression', [{'ax': 0, 'ce': 34, 'di': -2, 'ek': 5, 'fu': 12, 'gi': 27}],\n   {'ce': 3, 'fu': 1, 'gi': 2}),\n  ('normal control 1', [{'bo': 30, 'ek': 30, 'fu': 34, 'gi': 0, 'ho': -2}], {'bo': 2, 'ek': 2, 'fu': 3}),\n  ('normal control 2', [{'ce': 0, 'di': 30, 'ek': 34}], {'di': 2, 'ek': 3}),\n  ('normal control 3', [{'ce': 30, 'di': -2, 'fu': -2, 'gi': 0}], {'ce': 3}),\n  ('normal control 4', [{'ax': 30, 'bo': -2, 'ce': 30, 'ek': 30}], {'ax': 3, 'ce': 3, 'ek': 3})],\n [('regression: position consumption', [{'ax': 34, 'bo': 30, 'fu': -2, 'gi': 34, 'ho': 0}],\n   {'ax': 3, 'bo': 1, 'gi': 3}),\n  ('partial repair probe: position consumption', [{'bo': 34, 'ce': 34, 'ek': 30, 'fu': 26}],\n   {'bo': 3, 'ce': 3, 'ek': 1}),\n  ('second regression', [{'ax': 34, 'ce': 7, 'di': 0, 'gi': 34}], {'ax': 3, 'ce': 1, 'gi': 3}),\n  ('normal control 1', [{'ce': 0, 'gi': -2, 'ho': -2}], {}),\n  ('normal control 2', [{'ce': 12, 'ek': -2, 'fu': 29, 'ho': 12}], {'ce': 2, 'fu': 3, 'ho': 2}),\n  ('normal control 3', [{'ce': -2, 'ek': 34, 'fu': 12}], {'ek': 3, 'fu': 2}),\n  ('normal control 4', [{'ce': 34, 'di': -2, 'gi': 30}], {'ce': 3, 'gi': 2})],\n [('regression: position consumption', [{'ax': 34, 'bo': 12, 'ce': 34, 'di': 34, 'fu': 0, 'gi': 30, 'ho': 0}],\n   {'ax': 3, 'ce': 3, 'di': 3}),\n  ('partial repair probe: position consumption', [{'bo': 0, 'ce': 17, 'fu': 30, 'ho': 34}],\n   {'ce': 1, 'fu': 2, 'ho': 3}),\n  ('second regression', [{'ax': 34, 'ek': 28, 'gi': 30}], {'ax': 3, 'ek': 1, 'gi': 2}),\n  ('normal control 1', [{'ce': 34, 'di': 0, 'ek': 34}], {'ce': 3, 'ek': 3}),\n  ('normal control 2', [{'bo': -2, 'di': -2, 'fu': 24}], {'fu': 3}),\n  ('normal control 3', [{'ax': 0, 'di': 0, 'fu': 30, 'ho': 12}], {'fu': 3, 'ho': 2}),\n  ('normal control 4', [{'ax': 34, 'bo': -2, 'ce': -2, 'ek': 0, 'fu': 12, 'gi': 0, 'ho': -2}],\n   {'ax': 3, 'fu': 2})],\n [('regression: position consumption',\n   [{'ax': 12, 'bo': 34, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 12, 'gi': 34, 'ho': 27}],\n   {'bo': 3, 'ce': 3, 'gi': 3}),\n  ('partial repair probe: position consumption', [{'ax': 12, 'ce': 30, 'ek': 27, 'ho': -2}],\n   {'ax': 1, 'ce': 3, 'ek': 2}),\n  ('second regression', [{'ax': 27, 'bo': 0, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 27, 'gi': 30, 'ho': 0}],\n   {'ax': 1, 'ce': 3, 'fu': 1, 'gi': 2}),\n  ('normal control 1', [{'bo': 12, 'di': 34, 'fu': 0}], {'bo': 2, 'di': 3}),\n  ('normal control 2', [{'ax': 0, 'ce': 0, 'fu': -2}], {}),\n  ('normal control 3', [{'ax': 30, 'ek': 30, 'gi': 34}], {'ax': 2, 'ek': 2, 'gi': 3}),\n  ('normal control 4', [{'ce': -2, 'di': 0, 'fu': 34, 'ho': 34}], {'fu': 3, 'ho': 3})],\n [('regression: position consumption',\n   [{'ax': 12, 'bo': 34, 'ce': 0, 'di': 34, 'fu': 30, 'gi': 34, 'ho': 30}], {'bo': 3, 'di': 3, 'gi': 3}),\n  ('partial repair probe: position consumption',\n   [{'ax': 30, 'bo': 0, 'ce': 0, 'ek': 27, 'fu': 27, 'gi': 12, 'ho': 34}],\n   {'ax': 2, 'ek': 1, 'fu': 1, 'ho': 3}),\n  ('second regression', [{'ax': 27, 'ce': 8, 'di': 0, 'fu': 30, 'gi': -2}], {'ax': 2, 'ce': 1, 'fu': 3}),\n  ('normal control 1', [{'bo': 34, 'di': 27, 'ek': -2}], {'bo': 3, 'di': 2}),\n  ('normal control 2', [{'ax': 30, 'bo': 12, 'ce': 0, 'fu': 12, 'ho': 12}],\n   {'ax': 3, 'bo': 2, 'fu': 2, 'ho': 2}),\n  ('normal control 3', [{'ax': -2, 'ce': -2, 'di': -2, 'ek': -2}], {}),\n  ('normal control 4', [{'bo': -2, 'gi': 0, 'ho': 12}], {'ho': 3})]]\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 scoring contract stipulated for this example; it is not the rulebook of any real fantasy platform. 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-fantasy-sports-scoring-bonus-point-ranks-position-consumption","generated_at":"2026-09-29T14:50:38.761623+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Bonus allocation with ties is a compact but contested rule in football fantasy games.","repair":"Advance the position by the number of tied players.","root_cause":"The position counter advances by one per tie group instead of by group size.","sha256":"f578eaec59559bd54790530db7f245a8331cd96d643d580620168684c9564f9f","title":"Ties consume only one bonus position · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":44.47,"exit_code":1,"observations":[{"actual":{"bo":3,"ce":1,"ek":2,"fu":3},"check":"regression: position consumption","expected":{"bo":3,"ce":1,"fu":3},"passed":false},{"actual":{"ax":2,"ce":1,"di":2,"ek":1,"fu":1,"gi":3,"ho":2},"check":"partial repair probe: position consumption","expected":{"ax":1,"di":2,"gi":3,"ho":1},"passed":false},{"actual":{"ce":3,"ek":2,"fu":2,"gi":2},"check":"second regression","expected":{"ce":3,"fu":1,"gi":2},"passed":false},{"actual":{"bo":2,"ek":2,"fu":3},"check":"normal control 1","expected":{"bo":2,"ek":2,"fu":3},"passed":true},{"actual":{"di":2,"ek":3},"check":"normal control 2","expected":{"di":2,"ek":3},"passed":true},{"actual":{"ce":3},"check":"normal control 3","expected":{"ce":3},"passed":true},{"actual":{"ax":3,"ce":3,"ek":3},"check":"normal control 4","expected":{"ax":3,"ce":3,"ek":3},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: position consumption\", \"actual\": {\"bo\": 3, \"fu\": 3, \"ce\": 1, \"ek\": 2}, \"expected\": {\"bo\": 3, \"ce\": 1, \"fu\": 3}, \"passed\": false}, {\"check\": \"partial repair probe: position consumption\", \"actual\": {\"gi\": 3, \"di\": 2, \"ax\": 2, \"ho\": 2, \"ce\": 1, \"ek\": 1, \"fu\": 1}, \"expected\": {\"ax\": 1, \"di\": 2, \"gi\": 3, \"ho\": 1}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"ce\": 3, \"gi\": 2, \"fu\": 2, \"ek\": 2}, \"expected\": {\"ce\": 3, \"fu\": 1, \"gi\": 2}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"fu\": 3, \"bo\": 2, \"ek\": 2}, \"expected\": {\"bo\": 2, \"ek\": 2, \"fu\": 3}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"ek\": 3, \"di\": 2}, \"expected\": {\"di\": 2, \"ek\": 3}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"ce\": 3}, \"expected\": {\"ce\": 3}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"ax\": 3, \"ce\": 3, \"ek\": 3}, \"expected\": {\"ax\": 3, \"ce\": 3, \"ek\": 3}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":40.018,"exit_code":1,"observations":[{"actual":{"bo":3,"ce":2,"ek":1,"fu":3},"check":"regression: position consumption","expected":{"bo":3,"ce":1,"fu":3},"passed":false},{"actual":{"ax":1,"di":2,"gi":3,"ho":1},"check":"partial repair probe: position consumption","expected":{"ax":1,"di":2,"gi":3,"ho":1},"passed":true},{"actual":{"ce":3,"fu":1,"gi":2},"check":"second regression","expected":{"ce":3,"fu":1,"gi":2},"passed":true},{"actual":{"bo":2,"ek":2,"fu":3},"check":"normal control 1","expected":{"bo":2,"ek":2,"fu":3},"passed":true},{"actual":{"di":2,"ek":3},"check":"normal control 2","expected":{"di":2,"ek":3},"passed":true},{"actual":{"ce":3},"check":"normal control 3","expected":{"ce":3},"passed":true},{"actual":{"ax":3,"ce":3,"ek":3},"check":"normal control 4","expected":{"ax":3,"ce":3,"ek":3},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: position consumption\", \"actual\": {\"bo\": 3, \"fu\": 3, \"ce\": 2, \"ek\": 1}, \"expected\": {\"bo\": 3, \"ce\": 1, \"fu\": 3}, \"passed\": false}, {\"check\": \"partial repair probe: position consumption\", \"actual\": {\"gi\": 3, \"di\": 2, \"ax\": 1, \"ho\": 1}, \"expected\": {\"ax\": 1, \"di\": 2, \"gi\": 3, \"ho\": 1}, \"passed\": true}, {\"check\": \"second regression\", \"actual\": {\"ce\": 3, \"gi\": 2, \"fu\": 1}, \"expected\": {\"ce\": 3, \"fu\": 1, \"gi\": 2}, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": {\"fu\": 3, \"bo\": 2, \"ek\": 2}, \"expected\": {\"bo\": 2, \"ek\": 2, \"fu\": 3}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"ek\": 3, \"di\": 2}, \"expected\": {\"di\": 2, \"ek\": 3}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"ce\": 3}, \"expected\": {\"ce\": 3}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"ax\": 3, \"ce\": 3, \"ek\": 3}, \"expected\": 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