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fast-writing-style

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Use when revising a USENIX FAST paper for a storage contribution on the first page, a design/mechanism narrative a storage reviewer can follow, an evaluation framed as the storage cost it changes (write amplification, tail latency, endurance, crash consistency), double-blind wording, and disciplined use of the USENIX two-column page budget.

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FAST Writing Style

Use this when revising the main paper. FAST papers are read by storage systems people, so they need a storage contribution stated on the first page and an evaluation a storage reviewer trusts. The failure this skill prevents is a technically fine paper that reads like a general systems demo or a throughput-bar benchmark with "storage" in the title.

Revision rules

  • Lead with the storage contribution: the storage problem a practitioner recognizes, the storage cost current designs pay (write amplification, tail latency, endurance, space, or a consistency gap), your design or finding, real-device evidence, and what changes for storage systems.
  • Frame the evaluation as a cost you change, not a speed you win. State up front which storage quantity the paper moves; a reader should know by the end of the intro whether the headline is bytes-written, p99 latency, drive lifetime, or recovery correctness.
  • Pair every claim with proportional, real-device evidence — named drives and firmware, standard workloads/traces, a distribution not just a mean, a device counter not an estimate — not adjectives.
  • Make the device reality visible early. A storage reviewer wants to know the hardware and its state; a testbed table and a sentence on preconditioning/aging belong near the evaluation's start, not buried.
  • Protect the invariant. If the design defers, batches, or reorders writes, say early that you verify crash consistency/durability still holds; do not let the reader wonder.
  • Respect the USENIX page budget (FAST '27: ≤12 pages long / ≤6 short, references excluded) as a design constraint. It is a firm two-column limit; recover space editorially, never by shrinking the evaluation or the durability discussion.
  • Maintain double-blind in self-citations (third person), system/tool names, acknowledgements, funding, datacenter names, and trace-hosting URLs.

Storage paper skeleton

SectionJob it must doCommon failure
IntroStorage problem, the cost paid, contribution, evidence preview, storage payoff — first pageLeads with a technology trend, not a storage cost
BackgroundThe device/media/workload reality the design exploitsGeneric background not tied to the mechanism
Design / StudyThe mechanism or the study protocol, reproduciblyDesign described too thinly to rebuild
EvaluationEach claim answered with the right storage metric on real devicesThroughput bar standing in for the claimed cost
Consistency/durabilityThe invariant the change risks, testedConsistency asserted, never crash-tested
Related workDelta-first positioning against storage literatureCitation catalog with no contrast

Sentence-level rewrites

Draft patternFAST-safe rewrite
"Our system is much faster.""cuts write amplification from X to Y on <SSD model, firmware> at steady state"
"We evaluate on an SSD.""on <model/capacity/firmware>, preconditioned to steady state, fill Z%, TRIM on"
"Low latency.""p99.9 read latency of ... under ; full distribution in Fig. N"
"It is reliable / consistent.""recovers a consistent state at all injected crash points (§6)"
"State-of-the-art throughput."Claim scoped to the devices, workloads, and state actually tested
"We reduce writes by ~2x.""bytes-written from device counters fell 2.1x (95% CI ...), vs. the tuned baseline"

Storage-metric discipline

[Endurance]     report bytes-written / P/E cycles from device counters, not estimates
[Latency]       report the distribution (p50/p99/p99.9) under load, not the mean
[Amplification] separate read vs. write amplification; say how each is measured
[Space]         on-media footprint, including metadata/GC overhead
[Durability]    the crash-consistency invariant and the test that checks it
-> lead each result with the metric that matches the claim; put device+state beside it

Vignette: compressing a design-plus-study paper

A draft with a new cache design, six microbenchmarks, and a sprawling background: keep the design, the two experiments that carry the headline (miss-ratio-vs-cost and tail latency on real traces), and a crash-consistency check; move secondary microbenchmarks and full parameter sweeps to the artifact with forward references; cut background to the media/workload facts the mechanism needs. The test of a good cut: a reviewer should be able to answer "what storage cost does this change, by how much, on what hardware, and does it stay correct?" from the body alone.

Output format

[Writing diagnosis] clear / under-motivated / wrong-metric / device-reality-missing / over-scoped
[First-page fix] <new framing leading with the storage cost the paper changes>
[Metric audit] <claim -> storage metric -> measured on real devices? yes/no>
[Durability check placement] <where the crash-consistency/invariant test is stated>
[Anonymity edits] <system names / self-citations / trace URLs / datacenter names to rewrite>