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ieeesp-reproducibility

Use when hardening the reproducibility of an IEEE S&P (Oakland) paper's evidence before submission, including environment pinning for exploits and s…

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技能内容

IEEE S&P Reproducibility

Use this while the evidence is being produced — months before

ieeesp-artifact-evaluation packages it. Security results decay in ways ML

results do not: targets get patched, infrastructure changes, and an attack

that "worked in March" can be unreproducible by review time. Reproducibility

at S&P is first about freezing the world you measured.

Freeze the target, not just the code

| Evidence type | What must be pinned | Decay risk if not |

|---|---|---|

| Software exploit | Target version, build flags, distro, patch level | Silent fix ships mid-review |

| Microarchitectural attack | CPU model + stepping, microcode, OS mitigations state | Microcode update changes timing |

| Network measurement | Scan dates, vantage points, target-list snapshot | Internet moved; sample unrecoverable |

| Web/API study | Crawl date, client fingerprint, geographic origin | Server-side behavior shifts |

| ML attack/defense | Model weights hash, dataset version, threat-budget ε | "Same" model retrained differently |

Record these in the paper, not only in lab notes — a reviewer asking "does

this still work after <vendor>'s April update?" is a reproducibility question

about the world, and the answer is a documented snapshot date.

Determinism ledger for probabilistic evidence

Attacks with success probabilities, fuzzing campaigns, and randomized

defenses need trial discipline:

  • Report trials, not anecdotes: success rate over n runs with n stated,

plus dispersion — a "9/10 successful" exploit and a "measured once" exploit

are different claims.

  • Fuzzing comparisons follow the field's known pitfalls: equal CPU-time

budgets, multiple campaigns, identical seed corpora — state all three.

  • Randomized defenses (ASLR-like, moving-target): evaluate across the

randomness, not one lucky layout.

  • Timing measurements: report the noise floor and the machine's quiescence

conditions (isolated cores, frequency pinning) or the numbers will not

transfer.

Reproducibility ledger (one row per experiment in the paper):
  exp_id | claim it supports | target snapshot (ver/date/hw) |
  trials & seeds | dispersion reported? | rerun cost (time/hw/$) |
  rerunnable by outsider? (yes / gated / world-dependent)

The last column becomes the availability statement and the honest badge

target later.

When ethics limits release, say exactly what and why

S&P reviewers accept withheld material when the reasoning is specific:

  • "Exploit for CVE-pending issue withheld until the fix ships; released to

reviewers via the chairs on request" beats a silent gap.

  • User-derived datasets: describe schema and collection so others can

re-collect ethically, even when raw data cannot ship.

  • Never fabricate openness — a promised-but-empty repository found during

review or after publication is a reputation event, and at this venue

reviewers do check.

Cheap habits that pay at rebuttal time

  • One env.lock per experiment directory: container digest, package list,

kernel and microcode versions, dumped automatically by the run script.

  • Raw outputs archived before aggregation; the rebuttal question is always

about a number two steps upstream of the figure.

  • A regenerate_figures.sh that goes from archived raw data to every figure

— this is also the artifact-evaluation core later.

  • Date-stamped disclosure and measurement logs, because ethics questions in

review are answered with timelines (ieeesp-author-response).

What this venue does not require

Keep effort calibrated: S&P has no submission-time reproducibility checklist

in the verified 2026/2027 materials (待核实 each cycle), artifact evaluation

is post-acceptance and optional, and appendices are explicitly not

guaranteed reader attention. The reproducibility work above is therefore

aimed at three audiences in order: your own rebuttal, the shepherd, and the

AE committee — not at a submission-form requirement.

Output format

[Ledger status] <n>/<total> experiments with snapshot + trials + dispersion
[World-dependence] <which results cannot be re-run by anyone, ever — flagged in text?>
[Release plan] open / gated (reason) / withheld (reason) — per component
[Rebuttal readiness] raw data archived ✓/✗ · env locks ✓/✗ · figure regen ✓/✗
[Gaps to close before registration week] <ordered list>

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