{"abstract":"The tab workspace reports an incorrect icon footprint.","category":"Tab interfaces","checks":6,"contract":"Tab label layout reserves distinct icon, dirty marker, close button and padding footprints before truncating the title; absent decorations consume no width.","evaluation_group":"s3-tabs-tab-decoration-measurement","failed_approach":"The partial repair x['icon'] if x['icon_visible'] else 0 still violates a workspace boundary or normal case.","family":"s3-tab-interfaces-tab-decoration-measurement-icon-footprint","id":"FA-36481","implementations":{"attempt":{"sha256":"ab39aaad28b0499842e1c7104e0ab58f27f065f02c9faaa14e588851ee4dbcc4","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    r0 = x['icon'] if x['icon_visible'] else 0\n    r1 = x['dirty_width']+x['gap'] if x['dirty'] else 0\n    r2 = x['close_width']+x['gap'] if x['close'] else 0\n    r3 = 2*x['padding']\n    r4 = max(0,x['width']-2*x['padding']-(x['icon']+x['gap'] if x['icon_visible'] else 0)-(x['dirty_width']+x['gap'] if x['dirty'] else 0)-(x['close_width']+x['gap'] if x['close'] else 0))\n    r5 = x['title_width']>max(0,x['width']-2*x['padding']-(x['icon']+x['gap'] if x['icon_visible'] else 0)-(x['dirty_width']+x['gap'] if x['dirty'] else 0)-(x['close_width']+x['gap'] if x['close'] else 0))\n    return [r0,r1,r2,r3,r4,r5]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = {1: [({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 22, 16, 72, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': False, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [0, 10, 22, 16, 92, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': False, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 0, 22, 16, 82, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': False, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 0, 16, 94, True]), ({'width': 220, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 22, 16, 152, False]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 0, 'title_width': 110}, [16, 6, 18, 16, 84, True])], 2: [({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 44, 32, 144, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': False, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [0, 20, 44, 32, 184, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': False, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 0, 44, 32, 164, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': False, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 0, 32, 188, True]), ({'width': 440, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 44, 32, 304, False]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 0, 'title_width': 220}, [32, 12, 36, 32, 168, True])], 3: [({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 66, 48, 216, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': False, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [0, 30, 66, 48, 276, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': False, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 0, 66, 48, 246, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': False, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 0, 48, 282, True]), ({'width': 660, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 66, 48, 456, False]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 0, 'title_width': 330}, [48, 18, 54, 48, 252, True])], 4: [({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 88, 64, 288, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': False, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [0, 40, 88, 64, 368, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': False, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 0, 88, 64, 328, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': False, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 0, 64, 376, True]), ({'width': 880, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 88, 64, 608, False]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 0, 'title_width': 440}, [64, 24, 72, 64, 336, True])], 5: [({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 110, 80, 360, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': False, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [0, 50, 110, 80, 460, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': False, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 0, 110, 80, 410, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': False, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 0, 80, 470, True]), ({'width': 1100, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 110, 80, 760, False]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 0, 'title_width': 550}, [80, 30, 90, 80, 420, True])]}\nfor i, (inputs, expected) in enumerate(fixtures[N]):\n    check(\"workspace regression \"+str(i), solve(inputs), 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":"2a10b164d59f5709724bf3efc364d99040facd80ff0c67e985ca979c2e4fdabe","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    r0 = x['icon']+x['gap']\n    r1 = x['dirty_width']+x['gap'] if x['dirty'] else 0\n    r2 = x['close_width']+x['gap'] if x['close'] else 0\n    r3 = 2*x['padding']\n    r4 = max(0,x['width']-2*x['padding']-(x['icon']+x['gap'] if x['icon_visible'] else 0)-(x['dirty_width']+x['gap'] if x['dirty'] else 0)-(x['close_width']+x['gap'] if x['close'] else 0))\n    r5 = x['title_width']>max(0,x['width']-2*x['padding']-(x['icon']+x['gap'] if x['icon_visible'] else 0)-(x['dirty_width']+x['gap'] if x['dirty'] else 0)-(x['close_width']+x['gap'] if x['close'] else 0))\n    return [r0,r1,r2,r3,r4,r5]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = {1: [({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 22, 16, 72, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': False, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [0, 10, 22, 16, 92, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': False, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 0, 22, 16, 82, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': False, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 0, 16, 94, True]), ({'width': 220, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 22, 16, 152, False]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 0, 'title_width': 110}, [16, 6, 18, 16, 84, True])], 2: [({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 44, 32, 144, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': False, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [0, 20, 44, 32, 184, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': False, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 0, 44, 32, 164, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': False, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 0, 32, 188, True]), ({'width': 440, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 44, 32, 304, False]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 0, 'title_width': 220}, [32, 12, 36, 32, 168, True])], 3: [({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 66, 48, 216, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': False, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [0, 30, 66, 48, 276, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': False, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 0, 66, 48, 246, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': False, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 0, 48, 282, True]), ({'width': 660, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 66, 48, 456, False]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 0, 'title_width': 330}, [48, 18, 54, 48, 252, True])], 4: [({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 88, 64, 288, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': False, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [0, 40, 88, 64, 368, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': False, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 0, 88, 64, 328, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': False, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 0, 64, 376, True]), ({'width': 880, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 88, 64, 608, False]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 0, 'title_width': 440}, [64, 24, 72, 64, 336, True])], 5: [({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 110, 80, 360, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': False, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [0, 50, 110, 80, 460, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': False, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 0, 110, 80, 410, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': False, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 0, 80, 470, True]), ({'width': 1100, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 110, 80, 760, False]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 0, 'title_width': 550}, [80, 30, 90, 80, 420, True])]}\nfor i, (inputs, expected) in enumerate(fixtures[N]):\n    check(\"workspace regression \"+str(i), solve(inputs), 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":"dffa65f4bfdf716877b5400200194940c73514e0dcc7c240c11697cbfc8c3f1e","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    r0 = x['icon']+x['gap'] if x['icon_visible'] else 0\n    r1 = x['dirty_width']+x['gap'] if x['dirty'] else 0\n    r2 = x['close_width']+x['gap'] if x['close'] else 0\n    r3 = 2*x['padding']\n    r4 = max(0,x['width']-2*x['padding']-(x['icon']+x['gap'] if x['icon_visible'] else 0)-(x['dirty_width']+x['gap'] if x['dirty'] else 0)-(x['close_width']+x['gap'] if x['close'] else 0))\n    r5 = x['title_width']>max(0,x['width']-2*x['padding']-(x['icon']+x['gap'] if x['icon_visible'] else 0)-(x['dirty_width']+x['gap'] if x['dirty'] else 0)-(x['close_width']+x['gap'] if x['close'] else 0))\n    return [r0,r1,r2,r3,r4,r5]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = {1: [({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 22, 16, 72, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': False, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [0, 10, 22, 16, 92, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': False, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 0, 22, 16, 82, True]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': False, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 0, 16, 94, True]), ({'width': 220, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 4, 'title_width': 110}, [20, 10, 22, 16, 152, False]), ({'width': 140, 'padding': 8, 'icon': 16, 'icon_visible': True, 'dirty': True, 'dirty_width': 6, 'close': True, 'close_width': 18, 'gap': 0, 'title_width': 110}, [16, 6, 18, 16, 84, True])], 2: [({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 44, 32, 144, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': False, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [0, 20, 44, 32, 184, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': False, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 0, 44, 32, 164, True]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': False, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 0, 32, 188, True]), ({'width': 440, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 8, 'title_width': 220}, [40, 20, 44, 32, 304, False]), ({'width': 280, 'padding': 16, 'icon': 32, 'icon_visible': True, 'dirty': True, 'dirty_width': 12, 'close': True, 'close_width': 36, 'gap': 0, 'title_width': 220}, [32, 12, 36, 32, 168, True])], 3: [({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 66, 48, 216, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': False, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [0, 30, 66, 48, 276, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': False, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 0, 66, 48, 246, True]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': False, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 0, 48, 282, True]), ({'width': 660, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 12, 'title_width': 330}, [60, 30, 66, 48, 456, False]), ({'width': 420, 'padding': 24, 'icon': 48, 'icon_visible': True, 'dirty': True, 'dirty_width': 18, 'close': True, 'close_width': 54, 'gap': 0, 'title_width': 330}, [48, 18, 54, 48, 252, True])], 4: [({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 88, 64, 288, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': False, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [0, 40, 88, 64, 368, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': False, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 0, 88, 64, 328, True]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': False, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 0, 64, 376, True]), ({'width': 880, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 16, 'title_width': 440}, [80, 40, 88, 64, 608, False]), ({'width': 560, 'padding': 32, 'icon': 64, 'icon_visible': True, 'dirty': True, 'dirty_width': 24, 'close': True, 'close_width': 72, 'gap': 0, 'title_width': 440}, [64, 24, 72, 64, 336, True])], 5: [({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 110, 80, 360, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': False, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [0, 50, 110, 80, 460, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': False, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 0, 110, 80, 410, True]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': False, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 0, 80, 470, True]), ({'width': 1100, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 20, 'title_width': 550}, [100, 50, 110, 80, 760, False]), ({'width': 700, 'padding': 40, 'icon': 80, 'icon_visible': True, 'dirty': True, 'dirty_width': 30, 'close': True, 'close_width': 90, 'gap': 0, 'title_width': 550}, [80, 30, 90, 80, 420, True])]}\nfor i, (inputs, expected) in enumerate(fixtures[N]):\n    check(\"workspace regression \"+str(i), solve(inputs), 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":"Finite stipulated workspace snapshots only. Independent result fields describe observable obligations, not a full UI runtime. 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":"s3-tab-interfaces-tab-decoration-measurement-icon-footprint","generated_at":"2026-09-29T14:42:51.819431+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Offline tab/panel workspace behavior; no browser or desktop framework is emulated.","repair":"Use the stipulated workspace rule: x['icon']+x['gap'] if x['icon_visible'] else 0.","root_cause":"The icon footprint decision uses x['icon']+x['gap'] instead of x['icon']+x['gap'] if x['icon_visible'] else 0.","sha256":"62191324aa484dc7f122232437b4d7859d32a38160ef51f1ac409ae76948566a","title":"Tab decoration measurement: icon footprint · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":43.69,"exit_code":1,"observations":[{"actual":[16,10,22,16,72,true],"check":"workspace regression 0","expected":[20,10,22,16,72,true],"passed":false},{"actual":[0,10,22,16,92,true],"check":"workspace regression 1","expected":[0,10,22,16,92,true],"passed":true},{"actual":[16,0,22,16,82,true],"check":"workspace regression 2","expected":[20,0,22,16,82,true],"passed":false},{"actual":[16,10,0,16,94,true],"check":"workspace regression 3","expected":[20,10,0,16,94,true],"passed":false},{"actual":[16,10,22,16,152,false],"check":"workspace regression 4","expected":[20,10,22,16,152,false],"passed":false},{"actual":[16,6,18,16,84,true],"check":"workspace regression 5","expected":[16,6,18,16,84,true],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"workspace regression 0\", \"actual\": [16, 10, 22, 16, 72, true], \"expected\": [20, 10, 22, 16, 72, true], \"passed\": false}, {\"check\": \"workspace regression 1\", \"actual\": [0, 10, 22, 16, 92, true], \"expected\": [0, 10, 22, 16, 92, true], \"passed\": true}, {\"check\": \"workspace regression 2\", \"actual\": [16, 0, 22, 16, 82, true], \"expected\": [20, 0, 22, 16, 82, true], \"passed\": false}, {\"check\": \"workspace regression 3\", \"actual\": [16, 10, 0, 16, 94, true], \"expected\": [20, 10, 0, 16, 94, true], \"passed\": false}, {\"check\": \"workspace regression 4\", \"actual\": [16, 10, 22, 16, 152, false], \"expected\": [20, 10, 22, 16, 152, false], \"passed\": false}, {\"check\": \"workspace regression 5\", \"actual\": [16, 6, 18, 16, 84, true], \"expected\": [16, 6, 18, 16, 84, true], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.512,"exit_code":1,"observations":[{"actual":[20,10,22,16,72,true],"check":"workspace regression 0","expected":[20,10,22,16,72,true],"passed":true},{"actual":[20,10,22,16,92,true],"check":"workspace regression 1","expected":[0,10,22,16,92,true],"passed":false},{"actual":[20,0,22,16,82,true],"check":"workspace regression 2","expected":[20,0,22,16,82,true],"passed":true},{"actual":[20,10,0,16,94,true],"check":"workspace regression 3","expected":[20,10,0,16,94,true],"passed":true},{"actual":[20,10,22,16,152,false],"check":"workspace regression 4","expected":[20,10,22,16,152,false],"passed":true},{"actual":[16,6,18,16,84,true],"check":"workspace regression 5","expected":[16,6,18,16,84,true],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"workspace regression 0\", \"actual\": [20, 10, 22, 16, 72, true], \"expected\": [20, 10, 22, 16, 72, true], \"passed\": true}, {\"check\": \"workspace regression 1\", \"actual\": [20, 10, 22, 16, 92, true], \"expected\": [0, 10, 22, 16, 92, true], \"passed\": false}, {\"check\": \"workspace regression 2\", \"actual\": [20, 0, 22, 16, 82, true], \"expected\": [20, 0, 22, 16, 82, true], \"passed\": true}, {\"check\": \"workspace regression 3\", \"actual\": [20, 10, 0, 16, 94, true], \"expected\": [20, 10, 0, 16, 94, true], \"passed\": true}, {\"check\": \"workspace regression 4\", \"actual\": [20, 10, 22, 16, 152, false], \"expected\": [20, 10, 22, 16, 152, false], \"passed\": true}, {\"check\": \"workspace regression 5\", \"actual\": [16, 6, 18, 16, 84, true], \"expected\": [16, 6, 18, 16, 84, true], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":45.95,"exit_code":0,"observations":[{"actual":[20,10,22,16,72,true],"check":"workspace regression 0","expected":[20,10,22,16,72,true],"passed":true},{"actual":[0,10,22,16,92,true],"check":"workspace regression 1","expected":[0,10,22,16,92,true],"passed":true},{"actual":[20,0,22,16,82,true],"check":"workspace regression 2","expected":[20,0,22,16,82,true],"passed":true},{"actual":[20,10,0,16,94,true],"check":"workspace regression 3","expected":[20,10,0,16,94,true],"passed":true},{"actual":[20,10,22,16,152,false],"check":"workspace regression 4","expected":[20,10,22,16,152,false],"passed":true},{"actual":[16,6,18,16,84,true],"check":"workspace regression 5","expected":[16,6,18,16,84,true],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"workspace regression 0\", \"actual\": [20, 10, 22, 16, 72, true], \"expected\": [20, 10, 22, 16, 72, true], \"passed\": true}, {\"check\": \"workspace regression 1\", \"actual\": [0, 10, 22, 16, 92, true], \"expected\": [0, 10, 22, 16, 92, true], \"passed\": true}, {\"check\": \"workspace regression 2\", \"actual\": [20, 0, 22, 16, 82, true], \"expected\": [20, 0, 22, 16, 82, true], \"passed\": true}, {\"check\": \"workspace regression 3\", \"actual\": [20, 10, 0, 16, 94, true], \"expected\": [20, 10, 0, 16, 94, true], \"passed\": true}, {\"check\": \"workspace regression 4\", \"actual\": [20, 10, 22, 16, 152, false], \"expected\": [20, 10, 22, 16, 152, false], \"passed\": true}, {\"check\": \"workspace regression 5\", \"actual\": [16, 6, 18, 16, 84, true], \"expected\": [16, 6, 18, 16, 84, true], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}