{"abstract":"A gap exactly equal to jump distance is unreachable.","category":"Procedural level generation constraints","checks":8,"contract":"platforms [x1, x2, y] (y grows upward); the player starts on platform 0. From A the player reaches B when rise = yB-yA <= jump_h (any drop is allowed) and the horizontal gap max(0, xB1-xA2, xA1-xB2) <= jump_d - max(0, rise)//2. Reachability is transitive. Returns sorted reachable indices.","evaluation_group":"w2-procedural-level-generation-constraints-platform-jumps","failed_approach":"Excluding zero gaps disconnects overlapping platforms.","family":"w2-procedural-level-generation-constraints-platform-jumps-gap-boundary","id":"FA-86471","implementations":{"attempt":{"sha256":"f2d203ec9b0e7ae4857b1e6a041210c66cedd3bbbcaa76bc660ee35d0eec20f6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(platforms, jump_h, jump_d):\n    n = len(platforms)\n    seen = {0}\n    queue = [0]\n    while queue:\n        a = queue.pop(0)\n        ax1, ax2, ay = platforms[a]\n        for b in range(n):\n            if b in seen:\n                continue\n            bx1, bx2, by = platforms[b]\n            rise = by - ay\n            if rise > jump_h:\n                continue\n            gap = max(0, bx1 - ax2, ax1 - bx2)\n            reach = jump_d - max(0, rise) // 2\n            if gap <= reach and gap > 0:\n                seen.add(b)\n                queue.append(b)\n    return sorted(seen)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncases = [[('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('regression gap boundary #1',\n   [[[5, 9, 8], [7, 13, 0], [0, 2, 9], [13, 13, 2], [25, 31, 3]], 2, 1],\n   [0, 1, 3]),\n  ('regression gap boundary #2', [[[23, 29, 6], [19, 22, 0], [30, 32, 8], [15, 20, 1]], 3, 1], [0, 1, 3]),\n  ('partial repair boundary #1', [[[29, 30, 8], [13, 15, 5], [30, 33, 8]], 4, 6], [0, 2]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[13, 18, 6], [20, 22, 7]], 2, 8], [0, 1]),\n  ('control #2', [[[23, 29, 1], [3, 9, 0]], 4, 3], [0])],\n [('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('regression gap boundary #1',\n   [[[5, 9, 8], [7, 13, 0], [0, 2, 9], [13, 13, 2], [25, 31, 3]], 2, 1],\n   [0, 1, 3]),\n  ('regression gap boundary #2', [[[23, 29, 6], [19, 22, 0], [30, 32, 8], [15, 20, 1]], 3, 1], [0, 1, 3]),\n  ('partial repair boundary #1', [[[29, 30, 8], [13, 15, 5], [30, 33, 8]], 4, 6], [0, 2]),\n  ('partial repair boundary #2', [[[21, 21, 10], [16, 21, 3]], 4, 3], [0, 1]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[23, 29, 1], [3, 9, 0]], 4, 3], [0]),\n  ('control #2', [[[17, 20, 8]], 4, 4], [0])],\n [('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('fault site gap boundary #1',\n   [[[23, 25, 6], [15, 16, 2], [21, 21, 7], [27, 33, 3], [2, 8, 3]], 2, 2],\n   [0, 2, 3]),\n  ('regression gap boundary #1',\n   [[[18, 18, 5], [15, 19, 6], [21, 22, 3], [5, 9, 1], [14, 20, 6], [24, 29, 7]], 1, 5],\n   [0, 1, 2, 3, 4, 5]),\n  ('partial repair boundary #1', [[[7, 8, 6], [2, 8, 5], [20, 21, 2], [23, 28, 7]], 1, 5], [0, 1]),\n  ('partial repair boundary #2', [[[30, 35, 8], [29, 34, 7]], 1, 4], [0, 1]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[12, 14, 0], [26, 26, 2], [22, 27, 7], [0, 3, 1]], 5, 4], [0]),\n  ('control #2',\n   [[[19, 21, 8], [19, 19, 2], [21, 22, 10], [11, 17, 5], [11, 17, 9]], 3, 4],\n   [0, 1, 2, 3, 4])],\n [('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('fault site gap boundary #1',\n   [[[8, 11, 3], [22, 23, 8], [13, 13, 5], [26, 27, 3], [16, 16, 5]], 5, 3],\n   [0, 2, 4]),\n  ('regression gap boundary #1',\n   [[[3, 4, 8], [16, 18, 8], [9, 9, 2], [7, 12, 6], [19, 24, 7], [24, 27, 3]], 2, 5],\n   [0, 1, 2, 3, 4, 5]),\n  ('partial repair boundary #1', [[[30, 35, 8], [29, 34, 7]], 1, 4], [0, 1]),\n  ('partial repair boundary #2', [[[25, 26, 5], [19, 25, 6], [15, 19, 7]], 3, 3], [0, 1, 2]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[5, 5, 2]], 4, 6], [0]),\n  ('control #2', [[[27, 29, 10]], 3, 1], [0])],\n [('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('fault site gap boundary #1',\n   [[[11, 15, 6], [6, 8, 9], [28, 34, 2], [22, 24, 7], [4, 6, 5], [28, 34, 10]], 2, 5],\n   [0, 4]),\n  ('regression gap boundary #1',\n   [[[29, 34, 5], [6, 11, 2], [26, 26, 4], [25, 31, 2], [0, 2, 0], [5, 11, 5]], 2, 1],\n   [0, 2, 3]),\n  ('partial repair boundary #1',\n   [[[7, 9, 9], [10, 15, 0], [7, 10, 2], [9, 14, 4], [26, 30, 8], [15, 19, 1]], 5, 1],\n   [0, 1, 2, 3, 5]),\n  ('partial repair boundary #2',\n   [[[19, 24, 5], [30, 34, 4], [9, 14, 9], [16, 22, 8], [6, 6, 9]], 3, 4],\n   [0, 2, 3, 4]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[18, 20, 2], [24, 29, 0], [12, 17, 2], [30, 35, 0], [8, 12, 5]], 2, 7], [0, 1, 2, 3]),\n  ('control #2', [[[21, 24, 2], [4, 5, 1], [12, 12, 2]], 1, 8], [0])]]\nfor label, args, expected in cases[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":"48054b064fc6b70e0bfdb66332a4ae0ccb3d9db6123ff681373f0676b0e9c912","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(platforms, jump_h, jump_d):\n    n = len(platforms)\n    seen = {0}\n    queue = [0]\n    while queue:\n        a = queue.pop(0)\n        ax1, ax2, ay = platforms[a]\n        for b in range(n):\n            if b in seen:\n                continue\n            bx1, bx2, by = platforms[b]\n            rise = by - ay\n            if rise > jump_h:\n                continue\n            gap = max(0, bx1 - ax2, ax1 - bx2)\n            reach = jump_d - max(0, rise) // 2\n            if gap < reach:\n                seen.add(b)\n                queue.append(b)\n    return sorted(seen)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncases = [[('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('regression gap boundary #1',\n   [[[5, 9, 8], [7, 13, 0], [0, 2, 9], [13, 13, 2], [25, 31, 3]], 2, 1],\n   [0, 1, 3]),\n  ('regression gap boundary #2', [[[23, 29, 6], [19, 22, 0], [30, 32, 8], [15, 20, 1]], 3, 1], [0, 1, 3]),\n  ('partial repair boundary #1', [[[29, 30, 8], [13, 15, 5], [30, 33, 8]], 4, 6], [0, 2]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[13, 18, 6], [20, 22, 7]], 2, 8], [0, 1]),\n  ('control #2', [[[23, 29, 1], [3, 9, 0]], 4, 3], [0])],\n [('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('regression gap boundary #1',\n   [[[5, 9, 8], [7, 13, 0], [0, 2, 9], [13, 13, 2], [25, 31, 3]], 2, 1],\n   [0, 1, 3]),\n  ('regression gap boundary #2', [[[23, 29, 6], [19, 22, 0], [30, 32, 8], [15, 20, 1]], 3, 1], [0, 1, 3]),\n  ('partial repair boundary #1', [[[29, 30, 8], [13, 15, 5], [30, 33, 8]], 4, 6], [0, 2]),\n  ('partial repair boundary #2', [[[21, 21, 10], [16, 21, 3]], 4, 3], [0, 1]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[23, 29, 1], [3, 9, 0]], 4, 3], [0]),\n  ('control #2', [[[17, 20, 8]], 4, 4], [0])],\n [('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('fault site gap boundary #1',\n   [[[23, 25, 6], [15, 16, 2], [21, 21, 7], [27, 33, 3], [2, 8, 3]], 2, 2],\n   [0, 2, 3]),\n  ('regression gap boundary #1',\n   [[[18, 18, 5], [15, 19, 6], [21, 22, 3], [5, 9, 1], [14, 20, 6], [24, 29, 7]], 1, 5],\n   [0, 1, 2, 3, 4, 5]),\n  ('partial repair boundary #1', [[[7, 8, 6], [2, 8, 5], [20, 21, 2], [23, 28, 7]], 1, 5], [0, 1]),\n  ('partial repair boundary #2', [[[30, 35, 8], [29, 34, 7]], 1, 4], [0, 1]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[12, 14, 0], [26, 26, 2], [22, 27, 7], [0, 3, 1]], 5, 4], [0]),\n  ('control #2',\n   [[[19, 21, 8], [19, 19, 2], [21, 22, 10], [11, 17, 5], [11, 17, 9]], 3, 4],\n   [0, 1, 2, 3, 4])],\n [('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('fault site gap boundary #1',\n   [[[8, 11, 3], [22, 23, 8], [13, 13, 5], [26, 27, 3], [16, 16, 5]], 5, 3],\n   [0, 2, 4]),\n  ('regression gap boundary #1',\n   [[[3, 4, 8], [16, 18, 8], [9, 9, 2], [7, 12, 6], [19, 24, 7], [24, 27, 3]], 2, 5],\n   [0, 1, 2, 3, 4, 5]),\n  ('partial repair boundary #1', [[[30, 35, 8], [29, 34, 7]], 1, 4], [0, 1]),\n  ('partial repair boundary #2', [[[25, 26, 5], [19, 25, 6], [15, 19, 7]], 3, 3], [0, 1, 2]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[5, 5, 2]], 4, 6], [0]),\n  ('control #2', [[[27, 29, 10]], 3, 1], [0])],\n [('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('fault site gap boundary #1',\n   [[[11, 15, 6], [6, 8, 9], [28, 34, 2], [22, 24, 7], [4, 6, 5], [28, 34, 10]], 2, 5],\n   [0, 4]),\n  ('regression gap boundary #1',\n   [[[29, 34, 5], [6, 11, 2], [26, 26, 4], [25, 31, 2], [0, 2, 0], [5, 11, 5]], 2, 1],\n   [0, 2, 3]),\n  ('partial repair boundary #1',\n   [[[7, 9, 9], [10, 15, 0], [7, 10, 2], [9, 14, 4], [26, 30, 8], [15, 19, 1]], 5, 1],\n   [0, 1, 2, 3, 5]),\n  ('partial repair boundary #2',\n   [[[19, 24, 5], [30, 34, 4], [9, 14, 9], [16, 22, 8], [6, 6, 9]], 3, 4],\n   [0, 2, 3, 4]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[18, 20, 2], [24, 29, 0], [12, 17, 2], [30, 35, 0], [8, 12, 5]], 2, 7], [0, 1, 2, 3]),\n  ('control #2', [[[21, 24, 2], [4, 5, 1], [12, 12, 2]], 1, 8], [0])]]\nfor label, args, expected in cases[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":"94e7a3edf19382b94e1c8ef20cb570ff83d07c247487d3d5e9dc309a4ee984e9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(platforms, jump_h, jump_d):\n    n = len(platforms)\n    seen = {0}\n    queue = [0]\n    while queue:\n        a = queue.pop(0)\n        ax1, ax2, ay = platforms[a]\n        for b in range(n):\n            if b in seen:\n                continue\n            bx1, bx2, by = platforms[b]\n            rise = by - ay\n            if rise > jump_h:\n                continue\n            gap = max(0, bx1 - ax2, ax1 - bx2)\n            reach = jump_d - max(0, rise) // 2\n            if gap <= reach:\n                seen.add(b)\n                queue.append(b)\n    return sorted(seen)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncases = [[('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('regression gap boundary #1',\n   [[[5, 9, 8], [7, 13, 0], [0, 2, 9], [13, 13, 2], [25, 31, 3]], 2, 1],\n   [0, 1, 3]),\n  ('regression gap boundary #2', [[[23, 29, 6], [19, 22, 0], [30, 32, 8], [15, 20, 1]], 3, 1], [0, 1, 3]),\n  ('partial repair boundary #1', [[[29, 30, 8], [13, 15, 5], [30, 33, 8]], 4, 6], [0, 2]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[13, 18, 6], [20, 22, 7]], 2, 8], [0, 1]),\n  ('control #2', [[[23, 29, 1], [3, 9, 0]], 4, 3], [0])],\n [('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('regression gap boundary #1',\n   [[[5, 9, 8], [7, 13, 0], [0, 2, 9], [13, 13, 2], [25, 31, 3]], 2, 1],\n   [0, 1, 3]),\n  ('regression gap boundary #2', [[[23, 29, 6], [19, 22, 0], [30, 32, 8], [15, 20, 1]], 3, 1], [0, 1, 3]),\n  ('partial repair boundary #1', [[[29, 30, 8], [13, 15, 5], [30, 33, 8]], 4, 6], [0, 2]),\n  ('partial repair boundary #2', [[[21, 21, 10], [16, 21, 3]], 4, 3], [0, 1]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[23, 29, 1], [3, 9, 0]], 4, 3], [0]),\n  ('control #2', [[[17, 20, 8]], 4, 4], [0])],\n [('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('fault site gap boundary #1',\n   [[[23, 25, 6], [15, 16, 2], [21, 21, 7], [27, 33, 3], [2, 8, 3]], 2, 2],\n   [0, 2, 3]),\n  ('regression gap boundary #1',\n   [[[18, 18, 5], [15, 19, 6], [21, 22, 3], [5, 9, 1], [14, 20, 6], [24, 29, 7]], 1, 5],\n   [0, 1, 2, 3, 4, 5]),\n  ('partial repair boundary #1', [[[7, 8, 6], [2, 8, 5], [20, 21, 2], [23, 28, 7]], 1, 5], [0, 1]),\n  ('partial repair boundary #2', [[[30, 35, 8], [29, 34, 7]], 1, 4], [0, 1]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[12, 14, 0], [26, 26, 2], [22, 27, 7], [0, 3, 1]], 5, 4], [0]),\n  ('control #2',\n   [[[19, 21, 8], [19, 19, 2], [21, 22, 10], [11, 17, 5], [11, 17, 9]], 3, 4],\n   [0, 1, 2, 3, 4])],\n [('chain of hops #1', [[[0, 1, 0], [3, 4, 2], [6, 7, 4]], 2, 3], [0, 1, 2]),\n  ('fault site gap boundary #1',\n   [[[8, 11, 3], [22, 23, 8], [13, 13, 5], [26, 27, 3], [16, 16, 5]], 5, 3],\n   [0, 2, 4]),\n  ('regression gap boundary #1',\n   [[[3, 4, 8], [16, 18, 8], [9, 9, 2], [7, 12, 6], [19, 24, 7], [24, 27, 3]], 2, 5],\n   [0, 1, 2, 3, 4, 5]),\n  ('partial repair boundary #1', [[[30, 35, 8], [29, 34, 7]], 1, 4], [0, 1]),\n  ('partial repair boundary #2', [[[25, 26, 5], [19, 25, 6], [15, 19, 7]], 3, 3], [0, 1, 2]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[5, 5, 2]], 4, 6], [0]),\n  ('control #2', [[[27, 29, 10]], 3, 1], [0])],\n [('platform to the left #1', [[[10, 12, 0], [4, 7, 0]], 1, 3], [0, 1]),\n  ('fault site gap boundary #1',\n   [[[11, 15, 6], [6, 8, 9], [28, 34, 2], [22, 24, 7], [4, 6, 5], [28, 34, 10]], 2, 5],\n   [0, 4]),\n  ('regression gap boundary #1',\n   [[[29, 34, 5], [6, 11, 2], [26, 26, 4], [25, 31, 2], [0, 2, 0], [5, 11, 5]], 2, 1],\n   [0, 2, 3]),\n  ('partial repair boundary #1',\n   [[[7, 9, 9], [10, 15, 0], [7, 10, 2], [9, 14, 4], [26, 30, 8], [15, 19, 1]], 5, 1],\n   [0, 1, 2, 3, 5]),\n  ('partial repair boundary #2',\n   [[[19, 24, 5], [30, 34, 4], [9, 14, 9], [16, 22, 8], [6, 6, 9]], 3, 4],\n   [0, 2, 3, 4]),\n  ('deep drop #1', [[[0, 2, 10], [3, 5, 0]], 2, 2], [0, 1]),\n  ('control #1', [[[18, 20, 2], [24, 29, 0], [12, 17, 2], [30, 35, 0], [8, 12, 5]], 2, 7], [0, 1, 2, 3]),\n  ('control #2', [[[21, 24, 2], [4, 5, 1], [12, 12, 2]], 1, 8], [0])]]\nfor label, args, expected in cases[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":"Deterministic toy contract stipulated for this model; integer or exact arithmetic only, not a reproduction of any specific game engine. 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-procedural-level-generation-constraints-platform-jumps-gap-boundary","generated_at":"2026-09-29T14:50:49.929014+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Procedural generators silently emit unplayable or unfair levels when a single constraint check uses the wrong boundary, axis, neighborhood or update order; the defect is visible in exact generated geometry.","repair":"Restore `if gap <= reach:` at the gap boundary step.","root_cause":"The reach comparison is strict.","sha256":"718fd9787ae6234b77888ca598e58c677cfbdd175814aeb6d2810f8a1d21e7a2","title":"Platform jump reachability: Maximum-length jumps fail · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":41.154,"exit_code":1,"observations":[{"actual":[0,1],"check":"platform to the left #1","expected":[0,1],"passed":true},{"actual":[0,1,2],"check":"chain of hops #1","expected":[0,1,2],"passed":true},{"actual":[0],"check":"regression gap boundary #1","expected":[0,1,3],"passed":false},{"actual":[0,1],"check":"regression gap boundary #2","expected":[0,1,3],"passed":false},{"actual":[0],"check":"partial repair boundary #1","expected":[0,2],"passed":false},{"actual":[0,1],"check":"deep drop #1","expected":[0,1],"passed":true},{"actual":[0,1],"check":"control #1","expected":[0,1],"passed":true},{"actual":[0],"check":"control #2","expected":[0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"platform to the left #1\", \"actual\": [0, 1], \"expected\": [0, 1], \"passed\": true}, {\"check\": \"chain of hops #1\", \"actual\": [0, 1, 2], \"expected\": [0, 1, 2], \"passed\": true}, {\"check\": \"regression gap boundary #1\", \"actual\": [0], \"expected\": [0, 1, 3], \"passed\": false}, {\"check\": \"regression gap boundary #2\", \"actual\": [0, 1], \"expected\": [0, 1, 3], \"passed\": false}, {\"check\": \"partial repair boundary #1\", \"actual\": [0], \"expected\": [0, 2], \"passed\": false}, {\"check\": \"deep drop #1\", \"actual\": [0, 1], \"expected\": [0, 1], \"passed\": true}, {\"check\": \"control #1\", \"actual\": [0, 1], \"expected\": [0, 1], \"passed\": true}, {\"check\": \"control #2\", \"actual\": [0], \"expected\": [0], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":39.42,"exit_code":1,"observations":[{"actual":[0],"check":"platform to the left #1","expected":[0,1],"passed":false},{"actual":[0],"check":"chain of hops #1","expected":[0,1,2],"passed":false},{"actual":[0,1],"check":"regression gap boundary #1","expected":[0,1,3],"passed":false},{"actual":[0],"check":"regression gap boundary #2","expected":[0,1,3],"passed":false},{"actual":[0,2],"check":"partial repair boundary #1","expected":[0,2],"passed":true},{"actual":[0,1],"check":"deep drop #1","expected":[0,1],"passed":true},{"actual":[0,1],"check":"control #1","expected":[0,1],"passed":true},{"actual":[0],"check":"control #2","expected":[0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"platform to the left #1\", \"actual\": [0], \"expected\": [0, 1], \"passed\": false}, {\"check\": \"chain of hops #1\", \"actual\": [0], \"expected\": [0, 1, 2], \"passed\": false}, {\"check\": \"regression gap boundary #1\", \"actual\": [0, 1], \"expected\": [0, 1, 3], \"passed\": false}, {\"check\": \"regression gap boundary #2\", \"actual\": [0], \"expected\": [0, 1, 3], \"passed\": false}, {\"check\": \"partial repair boundary #1\", \"actual\": [0, 2], \"expected\": [0, 2], \"passed\": true}, {\"check\": 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