{"abstract":"The tab workspace reports an incorrect multiple boundary rebase.","category":"Tab interfaces","checks":6,"contract":"Dragging a selected set keeps its visual order, rebases drop boundary by every moved item before it, preserves anchor view and leaves unselected tabs ordered.","evaluation_group":"s3-tabs-multi-tab-drag","failed_approach":"The partial repair max(0,x['boundary']-len(x['selected'])) still violates a workspace boundary or normal case.","family":"s3-tab-interfaces-multi-tab-drag-multiple-boundary-rebase","id":"FA-36191","implementations":{"attempt":{"sha256":"4d221b01d3cfdc66f34544cb84c51a598395c20c159667901ce2ab4c5d76edb5","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    r0 = [t for t in x['tabs'] if t in x['selected']]\n    r1 = [t for t in x['tabs'] if t not in x['selected']]\n    r2 = max(0,x['boundary']-len(x['selected']))\n    r3 = x['anchor']\n    r4 = [t for t in x['tabs'] if t in x['selected']].index(x['anchor'])\n    r5 = list(range(x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']]),x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']])+len(x['selected'])))\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: [({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 0, 'd', 1, [0, 1]])], 2: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 0, 'd', 1, [0, 1]])], 3: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 0, 'd', 1, [0, 1]])], 4: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1', 'background2'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 0, 'd', 1, [0, 1]])], 5: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 0, 'd', 1, [0, 1]])]}\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":"6141f5d770fac01bc6f4c945ee47bd17c76a58c1a38f648bbdbd40a27fae0983","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    r0 = [t for t in x['tabs'] if t in x['selected']]\n    r1 = [t for t in x['tabs'] if t not in x['selected']]\n    r2 = max(0,x['boundary']-1)\n    r3 = x['anchor']\n    r4 = [t for t in x['tabs'] if t in x['selected']].index(x['anchor'])\n    r5 = list(range(x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']]),x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']])+len(x['selected'])))\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: [({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 0, 'd', 1, [0, 1]])], 2: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 0, 'd', 1, [0, 1]])], 3: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 0, 'd', 1, [0, 1]])], 4: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1', 'background2'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 0, 'd', 1, [0, 1]])], 5: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 0, 'd', 1, [0, 1]])]}\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":"a2ab14e01534687e9120f90715aeac8fb0416f22bc248832d319201dbbdea747","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    r0 = [t for t in x['tabs'] if t in x['selected']]\n    r1 = [t for t in x['tabs'] if t not in x['selected']]\n    r2 = x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']])\n    r3 = x['anchor']\n    r4 = [t for t in x['tabs'] if t in x['selected']].index(x['anchor'])\n    r5 = list(range(x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']]),x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']])+len(x['selected'])))\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: [({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e'], 0, 'd', 1, [0, 1]])], 2: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0'], 0, 'd', 1, [0, 1]])], 3: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1'], 0, 'd', 1, [0, 1]])], 4: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1', 'background2'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2'], 0, 'd', 1, [0, 1]])], 5: [({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['d', 'b'], 'boundary': 5, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'd', 1, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 2, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 1, 'd', 1, [1, 2]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['a', 'b'], 'boundary': 5, 'anchor': 'a'}, [['a', 'b'], ['c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'a', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 5, 'anchor': 'b'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 3, 'b', 0, [3, 4]]), ({'tabs': ['a', 'b', 'c', 'd', 'e', 'background0', 'background1', 'background2', 'background3'], 'selected': ['b', 'd'], 'boundary': 0, 'anchor': 'd'}, [['b', 'd'], ['a', 'c', 'e', 'background0', 'background1', 'background2', 'background3'], 0, 'd', 1, [0, 1]])]}\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-multi-tab-drag-multiple-boundary-rebase","generated_at":"2026-09-29T14:42:48.867525+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['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']]).","root_cause":"The multiple boundary rebase decision uses max(0,x['boundary']-1) instead of x['boundary']-sum(t in x['selected'] for t in x['tabs'][:x['boundary']]).","sha256":"28c65ed66fea6b70559e4214da16c11f54957ad0176b03d2ff44878007e8143d","title":"Multi tab drag: multiple boundary rebase · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":47.664,"exit_code":1,"observations":[{"actual":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"check":"workspace regression 0","expected":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"check":"workspace regression 1","expected":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],0,"d",1,[1,2]],"check":"workspace regression 2","expected":[["b","d"],["a","c","e"],1,"d",1,[1,2]],"passed":false},{"actual":[["a","b"],["c","d","e"],3,"a",0,[3,4]],"check":"workspace regression 3","expected":[["a","b"],["c","d","e"],3,"a",0,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],3,"b",0,[3,4]],"check":"workspace regression 4","expected":[["b","d"],["a","c","e"],3,"b",0,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],0,"d",1,[0,1]],"check":"workspace regression 5","expected":[["b","d"],["a","c","e"],0,"d",1,[0,1]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"workspace regression 0\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 1\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 2\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [1, 2]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 1, \"d\", 1, [1, 2]], \"passed\": false}, {\"check\": \"workspace regression 3\", \"actual\": [[\"a\", \"b\"], [\"c\", \"d\", \"e\"], 3, \"a\", 0, [3, 4]], \"expected\": [[\"a\", \"b\"], [\"c\", \"d\", \"e\"], 3, \"a\", 0, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 4\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"b\", 0, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"b\", 0, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 5\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [0, 1]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [0, 1]], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":43.525,"exit_code":1,"observations":[{"actual":[["b","d"],["a","c","e"],4,"d",1,[3,4]],"check":"workspace regression 0","expected":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"passed":false},{"actual":[["b","d"],["a","c","e"],4,"d",1,[3,4]],"check":"workspace regression 1","expected":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"passed":false},{"actual":[["b","d"],["a","c","e"],1,"d",1,[1,2]],"check":"workspace regression 2","expected":[["b","d"],["a","c","e"],1,"d",1,[1,2]],"passed":true},{"actual":[["a","b"],["c","d","e"],4,"a",0,[3,4]],"check":"workspace regression 3","expected":[["a","b"],["c","d","e"],3,"a",0,[3,4]],"passed":false},{"actual":[["b","d"],["a","c","e"],4,"b",0,[3,4]],"check":"workspace regression 4","expected":[["b","d"],["a","c","e"],3,"b",0,[3,4]],"passed":false},{"actual":[["b","d"],["a","c","e"],0,"d",1,[0,1]],"check":"workspace regression 5","expected":[["b","d"],["a","c","e"],0,"d",1,[0,1]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"workspace regression 0\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 4, \"d\", 1, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"passed\": false}, {\"check\": \"workspace regression 1\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 4, \"d\", 1, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"passed\": false}, {\"check\": \"workspace regression 2\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 1, \"d\", 1, [1, 2]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 1, \"d\", 1, [1, 2]], \"passed\": true}, {\"check\": \"workspace regression 3\", \"actual\": [[\"a\", \"b\"], [\"c\", \"d\", \"e\"], 4, \"a\", 0, [3, 4]], \"expected\": [[\"a\", \"b\"], [\"c\", \"d\", \"e\"], 3, \"a\", 0, [3, 4]], \"passed\": false}, {\"check\": \"workspace regression 4\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 4, \"b\", 0, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"b\", 0, [3, 4]], \"passed\": false}, {\"check\": \"workspace regression 5\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [0, 1]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [0, 1]], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":44.174,"exit_code":0,"observations":[{"actual":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"check":"workspace regression 0","expected":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"check":"workspace regression 1","expected":[["b","d"],["a","c","e"],3,"d",1,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],1,"d",1,[1,2]],"check":"workspace regression 2","expected":[["b","d"],["a","c","e"],1,"d",1,[1,2]],"passed":true},{"actual":[["a","b"],["c","d","e"],3,"a",0,[3,4]],"check":"workspace regression 3","expected":[["a","b"],["c","d","e"],3,"a",0,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],3,"b",0,[3,4]],"check":"workspace regression 4","expected":[["b","d"],["a","c","e"],3,"b",0,[3,4]],"passed":true},{"actual":[["b","d"],["a","c","e"],0,"d",1,[0,1]],"check":"workspace regression 5","expected":[["b","d"],["a","c","e"],0,"d",1,[0,1]],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"workspace regression 0\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 1\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"d\", 1, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 2\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 1, \"d\", 1, [1, 2]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 1, \"d\", 1, [1, 2]], \"passed\": true}, {\"check\": \"workspace regression 3\", \"actual\": [[\"a\", \"b\"], [\"c\", \"d\", \"e\"], 3, \"a\", 0, [3, 4]], \"expected\": [[\"a\", \"b\"], [\"c\", \"d\", \"e\"], 3, \"a\", 0, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 4\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"b\", 0, [3, 4]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 3, \"b\", 0, [3, 4]], \"passed\": true}, {\"check\": \"workspace regression 5\", \"actual\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [0, 1]], \"expected\": [[\"b\", \"d\"], [\"a\", \"c\", \"e\"], 0, \"d\", 1, [0, 1]], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}