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>