{"abstract":"Volume-density added initial and gap reduction returns a wrong result when the minimum gap is reached after time_to_reduce alone.","category":"Traffic signal timing plans","checks":8,"contract":"Input {min_green, added_per_act_tenths, max_initial, red_actuations, initial_gap_tenths, min_gap_tenths, time_before_reduction, time_to_reduce, call, t}. Variable initial = min(max_initial, max(min_green, ceil(actuations*added/10))) seconds. Gap reduction is timed from the conflicting call (a call before green start counts from 0): until time_before_reduction elapses the allowed gap is the initial gap; during time_to_reduce it falls linearly with the reduction amount truncated to whole tenths; afterwards it is the minimum gap. Return {initial, gap_tenths}.","contract_signature":"x","evaluation_group":"w2-traffic_signal_timing_plans-volume-density","failed_approach":"Taking the larger of the two periods still does not add them.","family":"w2-traffic_signal_timing_plans-volume-density-reduction-end","id":"FA-68021","implementations":{"attempt":{"sha256":"c53c8d1682f078ff4cd4824ce2ee75e7a8e85aa6b85bf91303fcae2705e298c5","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    m = x['min_green']\n    initial = min(x['max_initial'], max(m, -(-x['red_actuations'] * x['added_per_act_tenths'] // 10)))\n    g0, gm = x['initial_gap_tenths'], x['min_gap_tenths']\n    el = x['t'] - max(x['call'], 0)\n    if el <= x['time_before_reduction']:\n        gap = g0\n    elif el >= max(x['time_before_reduction'], x['time_to_reduce']):\n        gap = gm\n    else:\n        done = el - x['time_before_reduction']\n        gap = g0 - (g0 - gm) * done // x['time_to_reduce']\n    return {'initial': initial, 'gap_tenths': gap}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[({'min_green': 10, 'added_per_act_tenths': 25, 'max_initial': 14, 'red_actuations': 20, 'initial_gap_tenths': 35, 'min_gap_tenths': 10, 'time_before_reduction': 3, 'time_to_reduce': 6, 'call': 3, 't': 27}, {'initial': 14, 'gap_tenths': 10}), ({'min_green': 6, 'added_per_act_tenths': 10, 'max_initial': 12, 'red_actuations': 1, 'initial_gap_tenths': 50, 'min_gap_tenths': 10, 'time_before_reduction': 8, 'time_to_reduce': 19, 'call': 4, 't': 2}, {'initial': 6, 'gap_tenths': 50}), ({'min_green': 9, 'added_per_act_tenths': 25, 'max_initial': 17, 'red_actuations': 9, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 7, 'time_to_reduce': 23, 'call': -4, 't': 60}, {'initial': 17, 'gap_tenths': 20}), ({'min_green': 10, 'added_per_act_tenths': 10, 'max_initial': 16, 'red_actuations': 20, 'initial_gap_tenths': 30, 'min_gap_tenths': 20, 'time_before_reduction': 9, 'time_to_reduce': 15, 'call': 14, 't': 29}, {'initial': 16, 'gap_tenths': 26}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 5, 'added_per_act_tenths': 20, 'max_initial': 27, 'red_actuations': 18, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 13, 'time_to_reduce': 24, 'call': 7, 't': 33}, {'initial': 27, 'gap_tenths': 34}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28})], [({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 8, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 4, 'initial_gap_tenths': 30, 'min_gap_tenths': 15, 'time_before_reduction': 7, 'time_to_reduce': 17, 'call': 0, 't': 20}, {'initial': 8, 'gap_tenths': 19}), ({'min_green': 8, 'added_per_act_tenths': 10, 'max_initial': 29, 'red_actuations': 6, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 12, 'time_to_reduce': 15, 'call': 5, 't': 24}, {'initial': 8, 'gap_tenths': 36}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 5, 'added_per_act_tenths': 20, 'max_initial': 14, 'red_actuations': 3, 'initial_gap_tenths': 40, 'min_gap_tenths': 10, 'time_before_reduction': 15, 'time_to_reduce': 10, 'call': 14, 't': 39}, {'initial': 6, 'gap_tenths': 10}), ({'min_green': 8, 'added_per_act_tenths': 10, 'max_initial': 12, 'red_actuations': 14, 'initial_gap_tenths': 40, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 11, 'call': 7, 't': 49}, {'initial': 12, 'gap_tenths': 15}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 16, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 20, 'time_before_reduction': 3, 'time_to_reduce': 25, 'call': 1, 't': 20}, {'initial': 14, 'gap_tenths': 26})], [({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 4, 'added_per_act_tenths': 20, 'max_initial': 10, 'red_actuations': 13, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 21, 'call': 5, 't': 13}, {'initial': 10, 'gap_tenths': 40}), ({'min_green': 10, 'added_per_act_tenths': 25, 'max_initial': 28, 'red_actuations': 18, 'initial_gap_tenths': 30, 'min_gap_tenths': 10, 'time_before_reduction': 3, 'time_to_reduce': 30, 'call': 14, 't': 33}, {'initial': 28, 'gap_tenths': 20}), ({'min_green': 9, 'added_per_act_tenths': 10, 'max_initial': 19, 'red_actuations': 0, 'initial_gap_tenths': 30, 'min_gap_tenths': 10, 'time_before_reduction': 7, 'time_to_reduce': 20, 'call': 2, 't': 38}, {'initial': 9, 'gap_tenths': 10}), ({'min_green': 7, 'added_per_act_tenths': 15, 'max_initial': 19, 'red_actuations': 9, 'initial_gap_tenths': 50, 'min_gap_tenths': 10, 'time_before_reduction': 5, 'time_to_reduce': 15, 'call': 9, 't': 26}, {'initial': 14, 'gap_tenths': 18}), ({'min_green': 5, 'added_per_act_tenths': 20, 'max_initial': 10, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 10, 'time_before_reduction': 12, 'time_to_reduce': 9, 'call': 12, 't': 31}, {'initial': 10, 'gap_tenths': 17})], [({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 6, 'added_per_act_tenths': 20, 'max_initial': 26, 'red_actuations': 2, 'initial_gap_tenths': 35, 'min_gap_tenths': 20, 'time_before_reduction': 3, 'time_to_reduce': 14, 'call': 12, 't': 28}, {'initial': 6, 'gap_tenths': 22}), ({'min_green': 8, 'added_per_act_tenths': 25, 'max_initial': 24, 'red_actuations': 0, 'initial_gap_tenths': 30, 'min_gap_tenths': 15, 'time_before_reduction': 14, 'time_to_reduce': 27, 'call': 1, 't': 34}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 7, 'added_per_act_tenths': 10, 'max_initial': 29, 'red_actuations': 1, 'initial_gap_tenths': 35, 'min_gap_tenths': 10, 'time_before_reduction': 1, 'time_to_reduce': 21, 'call': 14, 't': 30}, {'initial': 7, 'gap_tenths': 18}), ({'min_green': 8, 'added_per_act_tenths': 25, 'max_initial': 28, 'red_actuations': 14, 'initial_gap_tenths': 40, 'min_gap_tenths': 10, 'time_before_reduction': 15, 'time_to_reduce': 30, 'call': 10, 't': 56}, {'initial': 28, 'gap_tenths': 10}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 30, 'red_actuations': 12, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 11, 'time_to_reduce': 25, 'call': -2, 't': 12}, {'initial': 24, 'gap_tenths': 40}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31})], [({'min_green': 4, 'added_per_act_tenths': 25, 'max_initial': 20, 'red_actuations': 9, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 6, 'time_to_reduce': 23, 'call': 2, 't': 17}, {'initial': 20, 'gap_tenths': 33}), ({'min_green': 5, 'added_per_act_tenths': 25, 'max_initial': 13, 'red_actuations': 11, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 16, 'call': 6, 't': 27}, {'initial': 13, 'gap_tenths': 26}), ({'min_green': 4, 'added_per_act_tenths': 15, 'max_initial': 17, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 14, 'time_to_reduce': 8, 'call': 3, 't': 50}, {'initial': 11, 'gap_tenths': 20}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 16, 'red_actuations': 4, 'initial_gap_tenths': 50, 'min_gap_tenths': 15, 'time_before_reduction': 10, 'time_to_reduce': 22, 'call': 5, 't': 28}, {'initial': 10, 'gap_tenths': 30}), ({'min_green': 8, 'added_per_act_tenths': 25, 'max_initial': 23, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 10, 'time_before_reduction': 3, 'time_to_reduce': 30, 'call': 3, 't': 53}, {'initial': 8, 'gap_tenths': 10})]]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check('timing oracle' + ' %d' % i, solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"299ed89a6d9b13c4b7233ef686581380f4aba4da5b11c11715da63becc847aaa","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    m = x['min_green']\n    initial = min(x['max_initial'], max(m, -(-x['red_actuations'] * x['added_per_act_tenths'] // 10)))\n    g0, gm = x['initial_gap_tenths'], x['min_gap_tenths']\n    el = x['t'] - max(x['call'], 0)\n    if el <= x['time_before_reduction']:\n        gap = g0\n    elif el >= x['time_to_reduce']:\n        gap = gm\n    else:\n        done = el - x['time_before_reduction']\n        gap = g0 - (g0 - gm) * done // x['time_to_reduce']\n    return {'initial': initial, 'gap_tenths': gap}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[({'min_green': 10, 'added_per_act_tenths': 25, 'max_initial': 14, 'red_actuations': 20, 'initial_gap_tenths': 35, 'min_gap_tenths': 10, 'time_before_reduction': 3, 'time_to_reduce': 6, 'call': 3, 't': 27}, {'initial': 14, 'gap_tenths': 10}), ({'min_green': 6, 'added_per_act_tenths': 10, 'max_initial': 12, 'red_actuations': 1, 'initial_gap_tenths': 50, 'min_gap_tenths': 10, 'time_before_reduction': 8, 'time_to_reduce': 19, 'call': 4, 't': 2}, {'initial': 6, 'gap_tenths': 50}), ({'min_green': 9, 'added_per_act_tenths': 25, 'max_initial': 17, 'red_actuations': 9, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 7, 'time_to_reduce': 23, 'call': -4, 't': 60}, {'initial': 17, 'gap_tenths': 20}), ({'min_green': 10, 'added_per_act_tenths': 10, 'max_initial': 16, 'red_actuations': 20, 'initial_gap_tenths': 30, 'min_gap_tenths': 20, 'time_before_reduction': 9, 'time_to_reduce': 15, 'call': 14, 't': 29}, {'initial': 16, 'gap_tenths': 26}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 5, 'added_per_act_tenths': 20, 'max_initial': 27, 'red_actuations': 18, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 13, 'time_to_reduce': 24, 'call': 7, 't': 33}, {'initial': 27, 'gap_tenths': 34}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28})], [({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 8, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 4, 'initial_gap_tenths': 30, 'min_gap_tenths': 15, 'time_before_reduction': 7, 'time_to_reduce': 17, 'call': 0, 't': 20}, {'initial': 8, 'gap_tenths': 19}), ({'min_green': 8, 'added_per_act_tenths': 10, 'max_initial': 29, 'red_actuations': 6, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 12, 'time_to_reduce': 15, 'call': 5, 't': 24}, {'initial': 8, 'gap_tenths': 36}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 5, 'added_per_act_tenths': 20, 'max_initial': 14, 'red_actuations': 3, 'initial_gap_tenths': 40, 'min_gap_tenths': 10, 'time_before_reduction': 15, 'time_to_reduce': 10, 'call': 14, 't': 39}, {'initial': 6, 'gap_tenths': 10}), ({'min_green': 8, 'added_per_act_tenths': 10, 'max_initial': 12, 'red_actuations': 14, 'initial_gap_tenths': 40, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 11, 'call': 7, 't': 49}, {'initial': 12, 'gap_tenths': 15}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 16, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 20, 'time_before_reduction': 3, 'time_to_reduce': 25, 'call': 1, 't': 20}, {'initial': 14, 'gap_tenths': 26})], [({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 4, 'added_per_act_tenths': 20, 'max_initial': 10, 'red_actuations': 13, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 21, 'call': 5, 't': 13}, {'initial': 10, 'gap_tenths': 40}), ({'min_green': 10, 'added_per_act_tenths': 25, 'max_initial': 28, 'red_actuations': 18, 'initial_gap_tenths': 30, 'min_gap_tenths': 10, 'time_before_reduction': 3, 'time_to_reduce': 30, 'call': 14, 't': 33}, {'initial': 28, 'gap_tenths': 20}), ({'min_green': 9, 'added_per_act_tenths': 10, 'max_initial': 19, 'red_actuations': 0, 'initial_gap_tenths': 30, 'min_gap_tenths': 10, 'time_before_reduction': 7, 'time_to_reduce': 20, 'call': 2, 't': 38}, {'initial': 9, 'gap_tenths': 10}), ({'min_green': 7, 'added_per_act_tenths': 15, 'max_initial': 19, 'red_actuations': 9, 'initial_gap_tenths': 50, 'min_gap_tenths': 10, 'time_before_reduction': 5, 'time_to_reduce': 15, 'call': 9, 't': 26}, {'initial': 14, 'gap_tenths': 18}), ({'min_green': 5, 'added_per_act_tenths': 20, 'max_initial': 10, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 10, 'time_before_reduction': 12, 'time_to_reduce': 9, 'call': 12, 't': 31}, {'initial': 10, 'gap_tenths': 17})], [({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 6, 'added_per_act_tenths': 20, 'max_initial': 26, 'red_actuations': 2, 'initial_gap_tenths': 35, 'min_gap_tenths': 20, 'time_before_reduction': 3, 'time_to_reduce': 14, 'call': 12, 't': 28}, {'initial': 6, 'gap_tenths': 22}), ({'min_green': 8, 'added_per_act_tenths': 25, 'max_initial': 24, 'red_actuations': 0, 'initial_gap_tenths': 30, 'min_gap_tenths': 15, 'time_before_reduction': 14, 'time_to_reduce': 27, 'call': 1, 't': 34}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 7, 'added_per_act_tenths': 10, 'max_initial': 29, 'red_actuations': 1, 'initial_gap_tenths': 35, 'min_gap_tenths': 10, 'time_before_reduction': 1, 'time_to_reduce': 21, 'call': 14, 't': 30}, {'initial': 7, 'gap_tenths': 18}), ({'min_green': 8, 'added_per_act_tenths': 25, 'max_initial': 28, 'red_actuations': 14, 'initial_gap_tenths': 40, 'min_gap_tenths': 10, 'time_before_reduction': 15, 'time_to_reduce': 30, 'call': 10, 't': 56}, {'initial': 28, 'gap_tenths': 10}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 30, 'red_actuations': 12, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 11, 'time_to_reduce': 25, 'call': -2, 't': 12}, {'initial': 24, 'gap_tenths': 40}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31})], [({'min_green': 4, 'added_per_act_tenths': 25, 'max_initial': 20, 'red_actuations': 9, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 6, 'time_to_reduce': 23, 'call': 2, 't': 17}, {'initial': 20, 'gap_tenths': 33}), ({'min_green': 5, 'added_per_act_tenths': 25, 'max_initial': 13, 'red_actuations': 11, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 16, 'call': 6, 't': 27}, {'initial': 13, 'gap_tenths': 26}), ({'min_green': 4, 'added_per_act_tenths': 15, 'max_initial': 17, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 14, 'time_to_reduce': 8, 'call': 3, 't': 50}, {'initial': 11, 'gap_tenths': 20}), ({'min_green': 5, 'added_per_act_tenths': 15, 'max_initial': 20, 'red_actuations': 7, 'initial_gap_tenths': 40, 'min_gap_tenths': 20, 'time_before_reduction': 10, 'time_to_reduce': 15, 'call': 3, 't': 20}, {'initial': 11, 'gap_tenths': 31}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 25, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 20, 'time_before_reduction': 8, 'time_to_reduce': 12, 'call': 0, 't': 40}, {'initial': 8, 'gap_tenths': 20}), ({'min_green': 8, 'added_per_act_tenths': 20, 'max_initial': 12, 'red_actuations': 9, 'initial_gap_tenths': 35, 'min_gap_tenths': 15, 'time_before_reduction': 5, 'time_to_reduce': 20, 'call': -4, 't': 12}, {'initial': 12, 'gap_tenths': 28}), ({'min_green': 6, 'added_per_act_tenths': 25, 'max_initial': 16, 'red_actuations': 4, 'initial_gap_tenths': 50, 'min_gap_tenths': 15, 'time_before_reduction': 10, 'time_to_reduce': 22, 'call': 5, 't': 28}, {'initial': 10, 'gap_tenths': 30}), ({'min_green': 8, 'added_per_act_tenths': 25, 'max_initial': 23, 'red_actuations': 3, 'initial_gap_tenths': 50, 'min_gap_tenths': 10, 'time_before_reduction': 3, 'time_to_reduce': 30, 'call': 3, 't': 53}, {'initial': 8, 'gap_tenths': 10})]]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check('timing oracle' + ' %d' % i, solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"A deterministic, bounded toy model with a stipulated contract; it makes no claim of conformance to any agency manual or standard. 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-traffic_signal_timing_plans-volume-density-reduction-end","generated_at":"2026-09-29T14:47:58.332376+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Signal timing arithmetic is exact and integer or rational; a wrong rule silently produces unsafe or inefficient timing plans.","root_cause":"The end of reduction ignores the time-before-reduction offset, so the gap snaps to the minimum early.","sha256":"80cf24a339457352adf5b36f233733924aa9ad8f2892625a1b1068205a8c06a5","title":"Volume-density added initial and gap reduction: the minimum gap is reached after time_to_reduce alone · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":38.346,"exit_code":1,"observations":[{"actual":{"gap_tenths":10,"initial":14},"check":"timing oracle 0","expected":{"gap_tenths":10,"initial":14},"passed":true},{"actual":{"gap_tenths":50,"initial":6},"check":"timing oracle 1","expected":{"gap_tenths":50,"initial":6},"passed":true},{"actual":{"gap_tenths":20,"initial":17},"check":"timing oracle 2","expected":{"gap_tenths":20,"initial":17},"passed":true},{"actual":{"gap_tenths":20,"initial":16},"check":"timing oracle 3","expected":{"gap_tenths":26,"initial":16},"passed":false},{"actual":{"gap_tenths":20,"initial":8},"check":"timing oracle 4","expected":{"gap_tenths":20,"initial":8},"passed":true},{"actual":{"gap_tenths":20,"initial":11},"check":"timing oracle 5","expected":{"gap_tenths":31,"initial":11},"passed":false},{"actual":{"gap_tenths":20,"initial":27},"check":"timing oracle 6","expected":{"gap_tenths":34,"initial":27},"passed":false},{"actual":{"gap_tenths":28,"initial":12},"check":"timing oracle 7","expected":{"gap_tenths":28,"initial":12},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"timing oracle 0\", \"actual\": {\"initial\": 14, \"gap_tenths\": 10}, \"expected\": {\"initial\": 14, \"gap_tenths\": 10}, \"passed\": true}, {\"check\": \"timing oracle 1\", \"actual\": {\"initial\": 6, \"gap_tenths\": 50}, \"expected\": {\"initial\": 6, \"gap_tenths\": 50}, \"passed\": true}, {\"check\": \"timing oracle 2\", \"actual\": {\"initial\": 17, \"gap_tenths\": 20}, \"expected\": {\"initial\": 17, \"gap_tenths\": 20}, \"passed\": true}, {\"check\": \"timing oracle 3\", \"actual\": {\"initial\": 16, \"gap_tenths\": 20}, \"expected\": {\"initial\": 16, \"gap_tenths\": 26}, \"passed\": false}, {\"check\": \"timing oracle 4\", \"actual\": {\"initial\": 8, \"gap_tenths\": 20}, \"expected\": {\"initial\": 8, \"gap_tenths\": 20}, \"passed\": true}, {\"check\": \"timing oracle 5\", \"actual\": {\"initial\": 11, \"gap_tenths\": 20}, \"expected\": {\"initial\": 11, \"gap_tenths\": 31}, \"passed\": false}, {\"check\": \"timing oracle 6\", \"actual\": {\"initial\": 27, \"gap_tenths\": 20}, \"expected\": {\"initial\": 27, \"gap_tenths\": 34}, \"passed\": false}, {\"check\": \"timing oracle 7\", \"actual\": {\"initial\": 12, \"gap_tenths\": 28}, \"expected\": {\"initial\": 12, \"gap_tenths\": 28}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":39.957,"exit_code":1,"observations":[{"actual":{"gap_tenths":10,"initial":14},"check":"timing oracle 0","expected":{"gap_tenths":10,"initial":14},"passed":true},{"actual":{"gap_tenths":50,"initial":6},"check":"timing oracle 1","expected":{"gap_tenths":50,"initial":6},"passed":true},{"actual":{"gap_tenths":20,"initial":17},"check":"timing oracle 2","expected":{"gap_tenths":20,"initial":17},"passed":true},{"actual":{"gap_tenths":20,"initial":16},"check":"timing oracle 3","expected":{"gap_tenths":26,"initial":16},"passed":false},{"actual":{"gap_tenths":20,"initial":8},"check":"timing oracle 4","expected":{"gap_tenths":20,"initial":8},"passed":true},{"actual":{"gap_tenths":20,"initial":11},"check":"timing oracle 5","expected":{"gap_tenths":31,"initial":11},"passed":false},{"actual":{"gap_tenths":20,"initial":27},"check":"timing oracle 6","expected":{"gap_tenths":34,"initial":27},"passed":false},{"actual":{"gap_tenths":28,"initial":12},"check":"timing oracle 7","expected":{"gap_tenths":28,"initial":12},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"timing oracle 0\", \"actual\": {\"initial\": 14, \"gap_tenths\": 10}, \"expected\": {\"initial\": 14, \"gap_tenths\": 10}, \"passed\": true}, {\"check\": \"timing oracle 1\", \"actual\": {\"initial\": 6, \"gap_tenths\": 50}, \"expected\": {\"initial\": 6, \"gap_tenths\": 50}, \"passed\": true}, {\"check\": \"timing oracle 2\", \"actual\": {\"initial\": 17, \"gap_tenths\": 20}, \"expected\": {\"initial\": 17, \"gap_tenths\": 20}, \"passed\": true}, {\"check\": \"timing oracle 3\", \"actual\": {\"initial\": 16, \"gap_tenths\": 20}, \"expected\": {\"initial\": 16, \"gap_tenths\": 26}, \"passed\": false}, {\"check\": \"timing oracle 4\", \"actual\": {\"initial\": 8, \"gap_tenths\": 20}, \"expected\": {\"initial\": 8, \"gap_tenths\": 20}, \"passed\": true}, {\"check\": \"timing oracle 5\", \"actual\": {\"initial\": 11, \"gap_tenths\": 20}, \"expected\": {\"initial\": 11, \"gap_tenths\": 31}, \"passed\": false}, {\"check\": \"timing oracle 6\", \"actual\": {\"initial\": 27, \"gap_tenths\": 20}, \"expected\": {\"initial\": 27, \"gap_tenths\": 34}, \"passed\": false}, {\"check\": \"timing oracle 7\", \"actual\": {\"initial\": 12, \"gap_tenths\": 28}, \"expected\": {\"initial\": 12, \"gap_tenths\": 28}, \"passed\": true}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}