Agent Skills
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tacas-experiments
GitHub指导TACAS工具论文实验设计，强调诚实可复现性。涵盖使用公共基准、公平基线配置、准确报告指标、结果健全性检查及Artifact验证，确保对比公正且结论可信。
Trigger Scenarios
设计TACAS评估实验
审计工具论文实证部分
准备SV-COMP风格任务集
构建公平基线对比
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tacas-experiments -g -y
SKILL.md
Frontmatter
{
"name": "tacas-experiments",
"description": "Use when designing or auditing a TACAS (ETAPS) evaluation, covering shared verification benchmarks (SV-COMP-style task sets), fair baseline configuration and equal time budgets, honest wall-clock\/scalability reporting on stated hardware, soundness checking of results, reproducibility on the clean artifact VM, and how a TACAS tool-paper evaluation differs from a SV-COMP competition entry."
}
TACAS Experiments
Use this before submission when the empirical story is not yet locked. TACAS reviewers are verification experts, and the evaluation is where a tool or algorithm is won or lost. The organizing principle is honest, reproducible comparison: the experiment must test the claim on shared benchmarks, against a fairly configured baseline, with every number reproducible in the artifact (mandatory for tool papers).
Evaluation audit
- Use community benchmarks. Draw tasks from established suites (e.g., SV-COMP task sets, model- checking or SMT benchmark libraries, prior tool distributions) rather than a private set of favourable inputs. A benchmark nobody else uses invites the "cherry-picked" reject.
- Configure baselines fairly. Compare against the strongest available competing tool, with a documented, equal time and memory budget on the same hardware. An untuned or crippled baseline is a scored weakness, and reviewers often know the baseline's authors.
- Report the right quantities. Solved/unsolved counts, wall-clock time with the timeout stated, memory, and the largest instance handled — not a single ratio. State the machine (CPU, RAM) and the number of repetitions for any variance.
- Check your results for soundness. Verification tools can be fast because they are wrong: report how you validated answers (cross-checking against a reference tool, witness validation, known expected verdicts), and disclose any incorrect results rather than hiding them.
- Reproduce in the artifact. Every table and figure must regenerate from a script in the artifact on the clean ETAPS VM; a tool paper whose numbers cannot be reproduced fails the mandatory artifact evaluation and endangers the paper.
- Bound external validity. Say which languages, property classes, or system sizes the results cover, and name the ones they do not.
Claim-to-evidence design table
| Verification claim | Matching evidence | Reject pattern avoided |
|---|---|---|
| "Verifies more tasks than prior tools" | Solved counts on a shared benchmark set vs a tuned baseline, equal timeout | "Evaluated on our own examples only" |
| "Faster / more scalable" | Wall-clock and memory across realistic sizes, hardware stated | "Speedup ratio with no timeout or machine given" |
| "Finds real bugs" | Reproducible counterexamples/witnesses on real code, validated | "Warnings with no confirmed true positives" |
| "Sound (or sound up to k)" | Correctness argument + no incorrect verdicts on a validation set | "Fast because it silently under-approximates" |
| "General technique" | Multiple property classes / languages + stated limits | "One benchmark family, claimed universal" |
Fair-comparison checklist
[Baseline] strongest competitor, latest version, cited; not a straw man
[Budget] identical timeout and memory limit for every tool; state them
[Hardware] one machine, described; note any parallelism and core counts
[Tasks] a named, shared benchmark set; report per-category, not just totals
[Validation] answers cross-checked / witnesses validated; incorrect results disclosed
[Determinism] fix seeds/options; report variance across repetitions where relevant
SV-COMP vs a TACAS tool-paper evaluation
TACAS hosts SV-COMP, but a competition entry and a tool-paper evaluation are different deliverables — do not conflate them:
- SV-COMP runs your verifier on the common task set under the organizers' harness and rules, and reports a ranked, uniform comparison across all participants; your contribution is a short competition paper plus a conforming tool.
- A tool paper is peer-reviewed prose making a specific claim about your tool, evaluated on benchmarks you justify, judged on contribution and a reproducible artifact — not on a leaderboard position. You may use SV-COMP benchmarks in a tool paper, but cite them and keep the comparison fair and reproducible.
Vignette: evaluating a new model checker
Suppose the paper claims a new checker verifies more C tasks than the prior tool. The matching plan: take a shared C benchmark set (with categories), run both tools with an identical timeout and memory limit on one stated machine, report per-category solved/unsolved and wall-clock, validate verdicts (cross-check disagreements, validate violation witnesses), disclose any wrong answers, state which property classes are out of scope, and ship a clean-VM artifact whose scripts regenerate every table.
Reporting floor
- Machine description, timeout, and memory limit for every experiment.
- Per-benchmark or per-category results, not only aggregate totals.
- A soundness/validation statement and honest disclosure of incorrect results.
- Artifact scripts that regenerate each table/figure on the ETAPS VM.
Output format
[Evaluation readiness] strong / adequate / weak
[Claim -> evidence map] <claim: benchmark set / metric / baseline>
[Baseline fairness] <baseline -> latest? equal budget? same hardware? documented?>
[Soundness] <validation method; any incorrect results disclosed? yes/no>
[Reproducibility] <every number regenerates on the clean VM? yes/no>
[Decision-critical next run] <one experiment or validation to add>
Version History
- 9f86f09 Current 2026-07-19 17:47
