sigmetrics-writing-style

SIGMETRICS Writing Style

Use this when revising the main paper. SIGMETRICS papers are POMACS journal articles read by

performance-evaluation specialists, so they need a **precise performance contribution stated on the

first page** and claims a reviewer can check. The failure this skill prevents is a paper that

reads like a systems demo (numbers, no model) or a theory paper with no systems relevance

(theorems, no validation).

Revision rules

• Lead with the performance contribution, stated rigorously: the systems-performance problem, a

precise metric (mean vs. tail latency, throughput, regret, energy), why current models/policies

fall short, the contribution (a model, policy, methodology — ideally with a proven bound), the

validation, and what changes for real systems.

• State assumptions where the result uses them. A theorem is only as strong as its assumptions;

name the arrival process, service distribution, independence, and stationarity your result needs,

and show they are plausible for the target system. Hidden assumptions are the fastest reject.

• Pair every quantitative claim with proportional evidence — a proof for an analytic claim, a

simulation whose curve matches the analysis, confidence intervals over repeated runs, effect

sizes for a comparison — not adjectives.

• Validate the model against measurement. The SIGMETRICS signature move is showing that the

analytic prediction and the measured/simulated data agree; a theorem with no validation, or a

measurement with no model, is half a paper.

• Respect the 20-page acmsmall budget as a design constraint. References are unlimited, but body

text, figures, and in-body appendices are not. A paper that only fits by shrinking the assumptions

or the validation is over-scoped.

• Maintain double-anonymity in self-citations, system names, trace provenance, and

acknowledgements (except in the Operational Systems Track).

Performance-evaluation paper skeleton

| Section | Job it must do | Common failure |

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

| Intro | Problem, precise metric, inadequacy, contribution, validation preview, systems payoff — first page | Leads with a trend and "improves performance," no metric or model |

| Model / System | The model and its assumptions, stated precisely and justified | Assumptions hidden or unjustified against the real workload |

| Analysis | Theorems/bounds with proofs (full proofs in an appendix) | A claimed bound with a hand-waved or incomplete proof |

| Validation | Analysis-vs-simulation agreement; measurement of the real system | A plot with no analytic comparison, or no confidence intervals |

| Evaluation | Baselines, fairly tuned; the systems payoff on real workloads | Untuned baseline; toy inputs; benchmark score as the whole result |

| Assumption validity / threats | Where assumptions hold and where they are stressed | Deferred or absent; no estimation-error / robustness discussion |

Sentence-level rewrites

| Draft pattern | SIGMETRICS-safe rewrite |

|---|---|

| "Our policy significantly improves performance." | "reduces p99 latency by X% (95% CI ...) over <tuned baseline> on <workload>, matching Thm. 1" |

| "We assume the standard queueing model." | "We assume M/G/1 with service-time distribution fit to the trace (§5.1, QQ-plot Fig. 6)" |

| "The bound holds in general." | "Thm. 1 holds under assumptions A1-A3; §6 quantifies degradation when A2 is violated" |

| "Simulation confirms our approach." | "the analytic p99 curve lies within the simulated confidence intervals across three distributions (Fig. 4)" |

| "State-of-the-art results." | Claim scoped to the metric, workload, and regime actually analyzed and measured |

Assumption-and-validation discipline

[Assumptions] list each (arrival, service, independence, stationarity); justify against the target
[Analysis]    prove the bound; put full derivations in an appendix within the reviewed pages
[Validation]  overlay analysis on simulation/measurement; report CIs and number of runs
[Robustness]  quantify what happens when an assumption is stressed (estimation error, heavy tails)
-> a theorem, its assumptions, and its validation are one unit -- present them together

Vignette: compressing a proof-plus-measurement paper

A draft with three theorems, a long simulator description, and a sprawling measurement section: keep

all three theorem statements and their assumptions in the body, move full proofs to an appendix with

forward references, keep the one figure showing analysis-vs-simulation agreement and the table with

the trace-driven payoff, and cut redundant simulator detail to the artifact. The test of a good cut:

a reviewer should be able to answer "what is claimed, under what assumptions, and does the

measurement back it?" from the body alone.

Output format

[Writing diagnosis] clear / under-specified-assumptions / unvalidated / over-claimed / over-scoped
[First-page fix] <new framing leading with the precise performance contribution>
[Assumption audit] <assumption -> stated? justified against workload? where used?>
[Validation fix] <theorem/claim -> analysis-vs-measurement evidence to add>
[Anonymity edits] <system names / self-citations / trace provenance to rewrite>