Systems Paper Writing

Systems Paper Writing: Paragraph-Level Structural Blueprint

Fine-grained structural guidance for writing 10–12 page systems papers targeting top systems venues: OSDI, SOSP, ASPLOS, NSDI, and EuroSys. This skill provides page allocation per section, paragraph-level blueprints, and writing patterns distilled from authoritative guides and best-paper analysis.

When to Use This Skill

Boundary: ml-paper-writing provides general writing philosophy, multi-venue templates, and citation verification. This skill focuses exclusively on paragraph-level structural blueprints for systems conferences.

Authoritative Sources

This blueprint synthesizes guidance from established systems researchers:

1. Levin & Redell — "How (and How Not) to Write a Good Systems Paper" (SOSP'83 PC Chairs, USENIX/ACM SIGOPS)
2. Irene Zhang (MSR/UW) — "Hints on how to write an SOSP paper" (SOSP/OSDI PC)
3. Gernot Heiser (UNSW, seL4) — Style Guide + Paper Writing Talk
4. Timothy Roscoe (ETH Zürich) — "Writing reviews for systems conferences"
5. Mike Dahlin (UT Austin/Google) — "Giving a Conference Talk"
6. Yi Ding — "How to write good systems papers?"
7. hzwer & DingXiaoH — WritingAIPaper (GitHub 1.3k+ stars)

Full citations and URLs: see references/section-blueprints.md.

12-Page Systems Paper Blueprint

Overview: Page Allocation

Abstract (150–250 words, 5 sentences)

Sentence 1: Problem context and importance
Sentence 2: Gap in existing approaches
Sentence 3: Key insight or thesis ("X is better for Y in environment Z")
Sentence 4: Summary of approach and key results
Sentence 5: Broader impact or availability

Source: Levin & Redell — "Can you state the new idea concisely? Use them in the abstract." Irene Zhang — "The abstract is harder to write because you cannot use terms or concepts you introduced in the paper."

S1 Introduction (1.5–2 pages)

Paragraph structure:

1. Problem statement (~0.5 page) — Establish the domain and why it matters. Use concrete numbers (cluster sizes, workload statistics, latency requirements).
2. Gap analysis (~0.5 page) — Enumerate specific gaps G1–Gn in existing systems. Each gap is one sentence with evidence.
3. Key insight (1 paragraph) — The thesis statement: "X is better for applications Y running in environment Z." (Irene Zhang formula)
4. Contributions (~0.5 page) — Numbered list of 3–5 concrete contributions. Each contribution is testable and maps to a section.

Writing pattern: hzwer Move 1 (Establish territory) → Move 2 (Find niche) → Move 3 (Occupy niche).

Source: Irene Zhang — "clearly state your target environment (Z) and application (Y)" + "clearly state why previous systems do not meet the needs"; Levin & Redell — "What exactly is the problem being solved?"

S2 Background & Motivation (1–1.5 pages)

Paragraph structure:

1. Technical background (~0.5 page) — Define terms and systems the reader needs. Follow Gernot Heiser's "define-before-use" principle.
2. Production observations (~0.5–1 page) — Present Observation 1, 2, 3 from real data or measurements. Each observation leads to a design insight.

Source: Irene Zhang — "clearly motivate Y and Z. Why is application Y important?"; Gernot Heiser — "define-before-use."

S3 Design (3–4 pages)

Paragraph structure:

1. System architecture overview (~0.5 page) — Architecture diagram first (Yi Ding: "draw a picture first"). One-paragraph walkthrough of major components and data flow.
2. Module-by-module design (~2–2.5 pages) — Each subsection: what the module does, the design choice made, alternatives considered, and why this choice wins.
3. Design alternatives and trade-offs (~0.5–1 page) — For each major decision, explicitly discuss what was not chosen and why.

Source: Irene Zhang — "Every design choice made in X should be discussed with alternatives and the reasons for the choice"; Levin & Redell — "What were the alternatives considered at various points, and why were the choices made?"

S4 Implementation (0.5–1 page)

1. Prototype description — Language, framework, LOC, integration with existing systems.
2. Key engineering decisions — Non-obvious implementation choices worth documenting.

Source: Levin & Redell — "Does the paper describe something that has actually been implemented?"; Irene Zhang — "explain how you constructed a prototype to test your hypothesis."

S5 Evaluation (3–4 pages)

Paragraph structure:

1. Experimental setup (~0.5 page) — Hardware, baselines, workloads, metrics. Enough detail to reproduce.
2. End-to-end comparison (~1–1.5 pages) — X vs baselines for application Y on environment Z. Main performance results.
3. Microbenchmarks / Ablation (~1–1.5 pages) — Isolate each design decision's contribution. Ablation experiments decompose the gains.
4. Scalability (~0.5 page) — Show behavior as problem size, cluster size, or load increases.

Critical rule (Irene Zhang): State every experimental conclusion three times:

• Section opening: hypothesis ("We expect X to outperform Y because...")
• Section closing: conclusion ("Results show X outperforms Y by Z%")
• Figure caption: evidence ("Figure N shows X achieves Z% better throughput than Y")

Two experiment types:

• Type 1: X vs baselines for Y on Z (end-to-end comparison)
• Type 2: Ablation — remove each design component to measure its individual impact

S6 Related Work (1 page)

• Group by methodology or approach, not by individual papers.
• For each group: what they do, what limitation remains, how your work differs.
• Use a comparison table when comparing 4+ systems on specific dimensions.

Source: Levin & Redell — "Are comparisons with previous work clear and explicit?"; Irene Zhang — use comparison tables.

S7 Conclusion (0.5 page)

Three sentences (Irene Zhang formula):

1. The hypothesis / problem addressed
2. The solution approach
3. The key result

Writing Patterns

Four reusable patterns for structuring systems papers. See references/writing-patterns.md for detailed examples.

Pattern 1: Gap Analysis (Lucid, ASPLOS'23)

Enumerate gaps G1–Gn in Introduction → map to answers A1–An in Design. Creates a clear contract with the reader.

Pattern 2: Observation-Driven (GFS, arXiv 2025)

Present production observations (O1–O3) in Motivation → derive design insights → build system around insights. Effective when you have real workload data.

Pattern 3: Contribution List (Blox, EuroSys'24; Sia, SOSP'23)