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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsBefore quoting a coding-agent benchmark score, identify and freeze the exact evaluation set and execution setup that produced it. A benchmark name alone is not enough: report the split and version or freeze date, the model-agent system, the harness and scoring rules, and what information the agent could access. A frozen set makes comparisons more repeatable; it does not prove the tasks are sound, uncontaminated, or sufficiently different to establish a leaderboard ranking.
What does a coding-agent score actually measure?
A score measures a configured system on a particular set of tasks under a particular evaluation procedure. It may reflect the model, but also the agent or scaffold that turns model output into actions, the tools it can use, the harness, and the rules used to decide whether a task was solved.
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For example, SWE-bench Verified’s full leaderboard includes results from different agent systems, while its bash-only mini-SWE-agent setup is intended for comparing language models under a more constrained setup. Those are not interchangeable measurements. Name the benchmark and split, then specify whether the result belongs to a model alone or to a model-agent-scaffold system. SWE-bench documentation
What should you freeze and disclose?
Freeze the evaluation boundary before running or publishing a comparison: the included tasks, the dataset version or date the set was fixed, the agent’s available inputs, and the procedure used to verify results. Record the execution configuration as well as the task set; changing either can change what the score means.
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- Tasks: benchmark, split, dataset version or freeze date, and the number of valid tasks in the denominator.
- System: exact model name, agent or scaffold, tools, harness, and configuration or release version.
- Inputs: what the agent was given, including task descriptions and repository context, and whether any task answers or ground truth were excluded.
- Scoring: success rule, test or verification procedure, treatment of invalid runs, and number of attempts.
- Comparison: whether the other score used the same tasks and configuration; for repeated runs, how results were aggregated.
SWE-bench-Live illustrates why split names and dates matter: it describes Lite and Verified as frozen for leaderboard comparisons while its test split receives newer issues. In an August 2026 update, it said verified submissions must provide agent trajectories so maintainers can check whether ground truth or other fields were exposed. A frozen membership boundary and a check on agent behavior address different risks; disclose both where applicable. SWE-bench-Live
Frozen, held-out, and refreshed are not synonyms
| Term | What it means | What it does not establish |
|---|---|---|
| Frozen | Task membership stays fixed for a declared release or comparison period. | That every task is valid, or that participants have never encountered its content. |
| Held-out | The split is not publicly accessible in the same way as a public partition. SWE-Bench Pro describes held-out tasks from 12 repositories, alongside public tasks from 11 repositories and commercial tasks from 18 proprietary repositories. | That leakage is impossible. Report the benchmark publisher’s access description rather than treating “held-out” as proof of zero exposure. |
| Refreshed | New tasks or a changed task set provide a newer evaluation population. | Like-for-like comparability with a different release. Identify the version boundary rather than silently combining results. |
SWE-Bench Pro says its held-out and commercial tasks are not publicly accessible. SWE-bench-Live’s use of frozen subsets alongside a newer test split shows that a benchmark can have different update policies for different partitions. SWE-Bench Pro documentation · SWE-bench-Live
Does a frozen holdout prove the benchmark is good?
No. Freezing stabilizes which tasks are counted; it does not certify that those tasks are clear, solvable, or tested appropriately. SWE-bench describes Verified as a 500-instance human-filtered subset whose annotators reviewed clarity, test patches, and solvability. That is evidence of a curation process, not a guarantee that every instance remains a reliable measure or is protected from exposure. SWE-bench documentation
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchOpenAI’s July 8, 2026 account of its audit reported design and contamination issues in SWE-bench Verified and said it no longer provided meaningful signal on software-development capability. The same article described flaws in SWE-Bench Pro and said OpenAI retracted its earlier recommendation to adopt it. In that account, human reviewers selected low-coverage tests as an issue for 9.4% of the benchmark, compared with 4.1% in the agent pipeline. These are findings attributed to OpenAI’s audit, not universal estimates for all coding-agent benchmarks. OpenAI’s audit account
The audit describes several ways repository tasks can mismeasure capability: an issue prompt may mislead or omit necessary detail, tests may be overly strict, and low-coverage tests may fail to check whether the intended behavior was implemented. Human collaboration among issue authors, implementers, and test authors can also leave issue descriptions, merged changes, and tests misaligned when treated as isolated tasks.
Why can two published scores be incomparable?
Matching benchmark names do not guarantee matching experiments. SWE-bench notes that mini-SWE-agent 1.x and 2.x results are not necessarily comparable: version 2 uses tool calling, while version 1 parses actions from output strings. Report the exact release and configuration rather than presenting both results as if only the model changed. SWE-bench documentation
Likewise, a public leaderboard can change over time. Save a dated leaderboard snapshot or run record with the result, particularly when quoting a live page. SWE-Bench Pro’s documentation describes long-horizon work that can take professional engineers hours to days, involve multiple files, and span public, held-out, and commercial partitions. Its page also reports Pass@1 results under a unified scaffold, including a 23.3% result for GPT-5 at the time reflected on the page; that is a page-specific historical figure, not a current standing. SWE-Bench Pro
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Does a small leaderboard gap prove one agent is better?
Not by itself. Rounded percentages hide which individual tasks each system solved and how much uncertainty remains. When per-instance outcomes are available, compare systems on paired tasks and report the denominator, attempts, and uncertainty rather than inferring a robust ordering from a small difference in aggregate scores.
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A September 2026 preprint examining public per-instance SWE-bench results found no statistically separated adjacent pairs among the top thirty Verified results under its specified exact paired McNemar tests. The paper cautions that failure to reject a difference does not prove equivalence. This result is specific to the submissions, available per-instance data, and statistical method it analyzed; it is not a general conclusion about all benchmarks or leaderboards. September 2026 preprint on paired SWE-bench comparisons
A reporting template for a score
Use a statement that makes the measured system and comparison boundary explicit:
On [benchmark and split], [named model and agent/scaffold] resolved [count/valid denominator] under [harness/configuration version] using [scoring rule], on the set frozen at [date/version]. The agent received [available inputs]; [verification or leakage controls] were applied. This result is [directly comparable/not directly comparable] to [comparison result] because [same/different setup details].
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If there were repeated trials, add the number of attempts and how the aggregate was calculated. If the comparison is close and task-level results are available, include paired outcomes and the limits of the statistical comparison.
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