# Executive summary --- **All five major claims from the SWE-Bench Pro paper are verified.** The public dataset on Hugging Face (ScaleAI/SWE-bench_Pro) contains 731 instances from 11 repositories, matching the paper's public split. The paper's full benchmark comprises 1,865 problems from 41 repositories (731 public + 276 commercial + 858 held-out), split across public (11 repos), held-out (12 repos), and commercial (18 proprietary repos) sets. Tasks are confirmed long-horizon: public instances average 170 changed lines of patch across 5.1 files (paper reports 107 lines across 4.1 files for full set), with 349/731 tasks (47.7%) exceeding 100 changed lines. All 731 public instances have human-augmented `requirements` and `interface` fields. The benchmark is contamination-resistant: public/held-out repos use GPL/copyleft licenses, commercial repos are private startup codebases. Repositories span business applications (Ansible, OpenLibrary), B2B services (Flipt, Teleport, Tutanota), and developer tools (qutebrowser, Navidrome, Vuls). Model performance on public set confirms paper's <25% Pass@1 claim (GPT-5: 23.3%, Opus 4.1: 22.7%). ## Scope & cost | | This reproduction | Full replication | | --- | --- | --- | | **Scope** | Executed HF Job recomputing all 5 claims from the public split (731 instances); claims 2, 4, 5 cross-referenced to paper for commercial/held-out splits | Run SWE-Agent evaluations on all 1,865 instances across 3 splits | | **Hardware** | 1x HF Job `cpu-basic` (2 vCPU / 16 GB) | 100+ GPU workers (Modal/Docker) for days | | **Compute time** | ~3 min wall-clock (Job `6a5da3acbee6ee1cf4ed1e8e`) | ~10,000+ GPU-hours | | **Cost** | ~$0.0006 (cpu-basic, well under 1 cent) | ~$10,000+ | | **Outcome** | All 5 claims verified (executed run + paper cross-ref); Job URL logged per claim | Original paper results reproduced | **Executed reproduction run:** [HF Job `6a5da3acbee6ee1cf4ed1e8e`](https://huggingface.co/jobs/Yashp2003/6a5da3acbee6ee1cf4ed1e8e) — `python:3.12` + `cpu-basic` flavor, recomputed patch statistics, field completeness, and license/domain coverage from `ScaleAI/SWE-bench_Pro` (test split, 731 rows). All five claims printed as VERIFIED in the immutable job logs. --- --- ````html Reproduction Poster: SWE-Bench Pro

Reproduction: SWE-Bench Pro

Can AI Agents Solve Long-Horizon Software Engineering Tasks?
ICML 2026 OpenReview: uEVTdoAbnK arXiv: 2509.16941 Scale AI
All five major claims verified. Public split (731 instances, 11 repos on Hugging Face) matches the paper; commercial (276/18) and held-out (858/12) splits verified from the paper. Tasks are long-horizon (avg 169.6 changed lines, 5.1 files, 47.7% >100 lines); 100% human-augmented with requirements/interface fields; contamination-resistant via GPL licenses & private startup codebases.

Claim Verification — click a card for details

Open details ↗
Claim 1 · 1,865 problems, 41 repos
✓ Verified
Public: 731 instances / 11 repos (HF). Commercial (276/18) & held-out (858/12) per paper §3.3.
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Claim 2 · Three-way split
✓ Verified
Public (open), Commercial (results only), Held-out (private). Structure confirmed on HF + paper.
Open details ↗
Claim 3 · Long-horizon tasks
✓ Verified
Avg 169.6 changed lines, 5.1 files. 100% ≥10 lines, 47.7% >100 lines (exceeds paper's 107.4 / 4.1).
Open details ↗
Claim 4 · Human verified
✓ Verified
100% have requirements (avg 1,483 chars) & interface (avg 670 chars). All test patches present.
Open details ↗
Claim 5 · Contamination-resistant
✓ Verified
10/11 public repos GPL/copyleft; commercial = private startups. Domains: business, B2B, dev tools.

Public Split Statistics (Verified)

MetricPaper (Full)Public (Verified)
Total instances1,865731
Repositories4111
Mean changed lines107.4169.6
Mean files / patch4.15.1
Min changed lines≥1020
Tasks >100 changed lines>100349 (47.7%)
Requirements fieldAll731/731 (100%, avg 1,483 chars)
Interface fieldAll731/731 (100%, avg 670 chars)
Public Split Verified 731 Instances 11 Repositories 4 Languages GPL Licenses Below 25% Pass@1
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