g0-c0 performance_met 0.97× baseline · parity within measurement noise
Code parent: ∅ (initial) → g0-c0 · Generation 0 · initial candidate (no parent code)
- Approach
- sorted-bisect
- Physical microVM & fork
- sb-01m55xgnr1xme51d4bab9bnnvs ← physically forked from paused VM sb-01m55xge5pz50x960atf55199r
- Source SHA256
- 050561b3483b7c632edfa14a9e1a07990507fc3e4ebb1c5d9506f25405c54c31
- Correctness tests
- 60/60 (phase: benchmark)
- Candidate / baseline median
- 6.942 ms (raw: 6.941600999999853) / 7.133 ms (raw: 7.133359000000006) · 0.97× baseline · parity within measurement noise
- Timing methodology
- Authoritative supervisor wall-clock minus null-roundtrip IPC overhead (3 distinct datasets) · single-shot root cross-check agreement=False
- Generation / evaluation wall
- 1446.533 ms (raw: 1446.5328600017529) / 624.402 ms (raw: 624.4016210002883)
- Selection outcome
- selected as revision parent of g1-c0; superseded by g1-c0 (historical K02 text corrected in view; raw summary.json unchanged)
- Model explanation
- Sort one list (b) and iterate over the other (a). For each element in a, use binary search to find how many elements in sorted b satisfy the sum constraints. This achieves O((N+M) log M) time complexity and handles duplicates correctly via indices.
Code · actual provider response
from bisect import bisect_left, bisect_right
def count_pairs(a: list[int], b: list[int], lower: int, upper: int) -> int:
if lower > upper:
return 0
# Sort a copy of b to avoid mutating the original
sorted_b = sorted(b)
count = 0
for x in a:
# Find range in sorted_b where lower <= x + y <= upper
# This implies y >= lower - x and y <= upper - x
low_bound = lower - x
high_bound = upper - x
left_idx = bisect_left(sorted_b, low_bound)
right_idx = bisect_right(sorted_b, high_bound)
count += right_idx - left_idx
return count
Feedback, methodology and raw execution
{
"feedback": {
"baseline_ms": 7.133359000000006,
"benchmark": {
"agreement": false,
"authoritative_timing": {
"candidate_samples_ms": [
5.001110000000253,
6.941600999999853,
7.56517699999959
],
"reliable_subtraction": true,
"samples": [
{
"candidate_adjusted_ms": 5.001110000000253,
"candidate_roundtrip_ms": 15.326602000000022,
"overhead_roundtrip_ms": 10.32549199999977,
"seed": 346874994,
"trusted_baseline_ms": 7.133359000000006
},
{
"candidate_adjusted_ms": 6.941600999999853,
"candidate_roundtrip_ms": 15.361346999999803,
"overhead_roundtrip_ms": 8.41974599999995,
"seed": 346874995,
"trusted_baseline_ms": 7.096870999999894
},
{
"candidate_adjusted_ms": 7.56517699999959,
"candidate_roundtrip_ms": 14.874905999999743,
"overhead_roundtrip_ms": 7.309729000000154,
"seed": 346874996,
"trusted_baseline_ms": 7.361566000000153
}
],
"trusted_baseline_samples_ms": [
7.133359000000006,
7.096870999999894,
7.361566000000153
]
},
"baseline_count": 111279790,
"baseline_reps_ms": [
9.103786999999919,
8.709018000000235,
8.419426000000119
],
"candidate_count": 111279790,
"candidate_reps_ms": [
9.360716999999852,
9.133873000000126,
9.475462000000157
],
"copies_per_rep": true,
"dataset": "generated inside the worker from the seed; verified by sha256 digest",
"digest": "3d93599ca651dc549bed51b59415f4782d1dd68777cf4933b11faed50740be83",
"expected_count": 111279790,
"limitations": [
"diagnostic worker timings are untrusted; selected score uses supervisor wall and a separate trusted baseline",
"candidate net timing subtracts noisy IPC/data-generation overhead; not a robust portable speedup",
"the root-side wall clock bounds that claim from outside but cannot fully isolate the candidate",
"single sandbox, single machine: not a portable benchmark claim"
],
"lower": -346874993,
"n": 20000,
"reps": 3,
"root_measurement": {
"baseline_net_ms": 14.478455000000334,
"baseline_wall_ms": 21.829110000000096,
"candidate_net_ms": 14.759982000000171,
"candidate_wall_ms": 22.110636999999933,
"method": "root supervisor wall clock around each bench round trip, minus an identical overhead-only probe (which='none')",
"note": "cross-check of the untrusted self-timing only: single-shot point estimates that include IPC, JSON and array-generation noise, not a statistical measure",
"overhead_wall_ms": 7.350654999999762
},
"seed": 346874993,
"statistic": "median of 3 supervisor-measured distinct-dataset repetitions; candidate IPC overhead estimated by same-dataset null roundtrip",
"timed_where": "authoritative: trusted supervisor wall; diagnostic *_reps_ms: inside untrusted worker",
"upper": 256194574,
"warmup": 1,
"worker_baseline_median_ms": 8.709018000000235,
"worker_candidate_median_ms": 9.360716999999852
},
"benchmark_n": 20000,
"candidate_ms": 6.941600999999853,
"compile_ok": true,
"detail": null,
"elapsed_ms": 392.5487909999998,
"error_subtype": null,
"error_type": "performance_met",
"errors": [],
"exception_type": null,
"phase": "benchmark",
"protocol": {
"budget_s": 20.0,
"candidate_path": "/workspace/candidate/solution.py",
"framing": "newline-delimited JSON, one request object and one response object per line",
"output_caps_bytes": {
"max_line": 4194304,
"max_total": 16777216
},
"request_cap_bytes": 16777216,
"runs_as_user": "nobody",
"spawn": "runuser -u nobody -- env -i <minimal env> python3 -I worker.py",
"supervisor_imports_candidate": false,
"version": 1,
"worker_imports_candidate": true,
"worker_path": "/workspace/.kiss_trusted/worker.py"
},
"protocol_version": 1,
"seed": 1729,
"speedup": 1.0276244630021456,
"status": "performance_met",
"supervisor_self_protect": {
"mode": "0o400",
"path": "/workspace/.kiss_trusted/harness.py"
},
"tests_passed": 60,
"total": 60,
"worker": {
"numpy": false,
"pid": null,
"python": "3.12.3",
"user": "nobody"
}
},
"execution": {
"standard_output": "{\"baseline_ms\": 7.133359000000006, \"benchmark\": {\"agreement\": false, \"authoritative_timing\": {\"candidate_samples_ms\": [5.001110000000253, 6.941600999999853, 7.56517699999959], \"reliable_subtraction\": true, \"samples\": [{\"candidate_adjusted_ms\": 5.001110000000253, \"candidate_roundtrip_ms\": 15.326602000000022, \"overhead_roundtrip_ms\": 10.32549199999977, \"seed\": 346874994, \"trusted_baseline_ms\": 7.133359000000006}, {\"candidate_adjusted_ms\": 6.941600999999853, \"candidate_roundtrip_ms\": 15.361346999999803, \"overhead_roundtrip_ms\": 8.41974599999995, \"seed\": 346874995, \"trusted_baseline_ms\": 7.096870999999894}, {\"candidate_adjusted_ms\": 7.56517699999959, \"candidate_roundtrip_ms\": 14.874905999999743, \"overhead_roundtrip_ms\": 7.309729000000154, \"seed\": 346874996, \"trusted_baseline_ms\": 7.361566000000153}], \"trusted_baseline_samples_ms\": [7.133359000000006, 7.096870999999894, 7.361566000000153]}, \"baseline_count\": 111279790, \"baseline_reps_ms\": [9.103786999999919, 8.709018000000235, 8.419426000000119], \"candidate_count\": 111279790, \"candidate_reps_ms\": [9.360716999999852, 9.133873000000126, 9.475462000000157], \"copies_per_rep\": true, \"dataset\": \"generated inside the worker from the seed; verified by sha256 digest\", \"digest\": \"3d93599ca651dc549bed51b59415f4782d1dd68777cf4933b11faed50740be83\", \"expected_count\": 111279790, \"limitations\": [\"diagnostic worker timings are untrusted; selected score uses supervisor wall and a separate trusted baseline\", \"candidate net timing subtracts noisy IPC/data-generation overhead; not a robust portable speedup\", \"the root-side wall clock bounds that claim from outside but cannot fully isolate the candidate\", \"single sandbox, single machine: not a portable benchmark claim\"], \"lower\": -346874993, \"n\": 20000, \"reps\": 3, \"root_measurement\": {\"baseline_net_ms\": 14.478455000000334, \"baseline_wall_ms\": 21.829110000000096, \"candidate_net_ms\": 14.759982000000171, \"candidate_wall_ms\": 22.110636999999933, \"method\": \"root supervisor wall clock around each bench round trip, minus an identical overhead-only probe (which='none')\", \"note\": \"cross-check of the untrusted self-timing only: single-shot point estimates that include IPC, JSON and array-generation noise, not a statistical measure\", \"overhead_wall_ms\": 7.350654999999762}, \"seed\": 346874993, \"statistic\": \"median of 3 supervisor-measured distinct-dataset repetitions; candidate IPC overhead estimated by same-dataset null roundtrip\", \"timed_where\": \"authoritative: trusted supervisor wall; diagnostic *_reps_ms: inside untrusted worker\", \"upper\": 256194574, \"warmup\": 1, \"worker_baseline_median_ms\": 8.709018000000235, \"worker_candidate_median_ms\": 9.360716999999852}, \"benchmark_n\": 20000, \"candidate_ms\": 6.941600999999853, \"compile_ok\": true, \"detail\": null, \"elapsed_ms\": 392.5487909999998, \"error_subtype\": null, \"error_type\": \"performance_met\", \"errors\": [], \"exception_type\": null, \"phase\": \"benchmark\", \"protocol\": {\"budget_s\": 20.0, \"candidate_path\": \"/workspace/candidate/solution.py\", \"framing\": \"newline-delimited JSON, one request object and one response object per line\", \"output_caps_bytes\": {\"max_line\": 4194304, \"max_total\": 16777216}, \"request_cap_bytes\": 16777216, \"runs_as_user\": \"nobody\", \"spawn\": \"runuser -u nobody -- env -i <minimal env> python3 -I worker.py\", \"supervisor_imports_candidate\": false, \"version\": 1, \"worker_imports_candidate\": true, \"worker_path\": \"/workspace/.kiss_trusted/worker.py\"}, \"protocol_version\": 1, \"seed\": 1729, \"speedup\": 1.0276244630021456, \"status\": \"performance_met\", \"supervisor_self_protect\": {\"mode\": \"0o400\", \"path\": \"/workspace/.kiss_trusted/harness.py\"}, \"tests_passed\": 60, \"total\": 60, \"worker\": {\"numpy\": false, \"pid\": null, \"python\": \"3.12.3\", \"user\": \"nobody\"}}\n",
"standard_error": "harness status=performance_met phase=benchmark tests=60/60 elapsed=393ms\n",
"exit_code": 0,
"error_message": ""
}
}