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Rigorous Cloud System Evaluation Guidelines
socc-experiments
brycewang-stanford/Awesome-Journal-Skills
66
This guide provides comprehensive best practices for designing and auditing cloud system evaluations, particularly for academic submissions. It mandates that claims must be supported by measured evidence from real or realistic deployments, moving beyond simple simulations. Key metrics emphasized include tail latency (p99), operational cost modeling, and verifiable behavior under scale and multi-tenancy.
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Writing Related Work for SoCC Submissions
socc-related-work
brycewang-stanford/Awesome-Journal-Skills
319
A comprehensive guide for positioning a paper for ACM SoCC. It instructs authors to write the related work section by bridging both systems literature (e.g., OSDI, NSDI) and data-management literature (e.g., SIGMOD, VLDB). Focus must be on stating the 'delta'—the unique difference—rather than merely listing citations, ensuring dual anonymity and covering all relevant technical lanes.
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Ensuring Scientific Reproducibility in Systems Papers
socc-reproducibility
brycewang-stanford/Awesome-Journal-Skills
58
This comprehensive guide outlines best practices for achieving high levels of scientific reproducibility in systems papers, especially for cloud measurement studies. It teaches authors how to map every claim in their paper to verifiable evidence, detailing the entire testbed setup, reproducing tail latency and costs accurately, and maintaining consistency between reported numbers and artifacts.
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Modeling The SoCC Review Process
socc-review-process
brycewang-stanford/Awesome-Journal-Skills
181
This guide details the rigorous academic review process for ACM Symposium on Cloud Computing (SoCC) submissions. It explains the dual-anonymous, two-round review structure, the importance of incorporating both systems performance and data measurement rigor (including tail latency and cost), and how the rebuttal period functions. Essential reading for authors aiming to publish in top-tier cloud computing venues.
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SoCC Paper Submission Audit Checklist
socc-submission
brycewang-stanford/Awesome-Journal-Skills
486
A comprehensive audit guide for submitting research papers to ACM SoCC (Symposium on Cloud Computing). It covers critical aspects including the unique two-round deadlines, strict ACM formatting (12/6 pages, acmart template), dual-anonymous review requirements, identity leak prevention, and ensuring systems/data reproducibility posture before submission.
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Structuring Papers: Body Versus Supplementary Artifacts
socc-supplementary
brycewang-stanford/Awesome-Journal-Skills
497
A comprehensive guide for authors submitting technical papers to top-tier conferences, detailing how to effectively partition content between the main paper body and supplementary artifacts. It emphasizes the critical rule that all decision-making evidence (e.g., headline results, key performance metrics) must reside within the limited page budget of the main submission, ensuring the work is judgeable even without accessing raw data.
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Academic Cloud Research Venue Selection
socc-topic-selection
brycewang-stanford/Awesome-Journal-Skills
409
This guide helps researchers determine the ideal venue for their cloud computing research paper. It outlines the architectural boundaries between pure systems (OSDI/SOSP), pure data management (SIGMOD/VLDB), and the systems-data intersection (SoCC). It provides crucial tests, such as the model-swap and re-label tests, and advises on necessary evidence maturity (measurement studies, experience papers) to ensure a high chance of acceptance.
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Cloud Systems Conference Submission Workflow
socc-workflow
brycewang-stanford/Awesome-Journal-Skills
299
A detailed project management guide for submitting research papers to major cloud computing conferences like ACM SoCC. This workflow covers the entire lifecycle, from initial venue selection and evidence locking to abstract submission, rebuttal, and final acceptance. It provides critical backward planning heuristics and warns authors about common pitfall areas, such as insufficient measurement rigor or poor anonymity handling.
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SoCC Paper Writing Style Guide
socc-writing-style
brycewang-stanford/Awesome-Journal-Skills
67
This comprehensive guide provides strict structural and technical guidelines for authors submitting papers to ACM SoCC. It mandates focusing on cloud-scale problems recognized by operators, emphasizing contributions at the intersection of systems and data. Key requirements include reporting tail latency (p95/p99) and concrete cost models, grounding every claim in measured, real-world evidence, and explicitly stating external limitations.
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Publishing Guide for Chinese Social Sciences
social-sciences-in-china
brycewang-stanford/Awesome-Journal-Skills
299
This guide helps researchers understand the rigorous standards for publishing in the highly prestigious and cross-disciplinary journal, Social Sciences in China. It emphasizes that the core contribution must be theoretical depth, addressing major societal issues, and developing original concepts, rather than merely demonstrating advanced empirical techniques or niche findings.
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Social Security Journal Submission Guide
social-security-studies
brycewang-stanford/Awesome-Journal-Skills
431
This skill is a comprehensive guide for authors targeting the journal *Social Security Studies*. It analyzes the journal's specific fit, required methodology, core themes (such as pension, medical insurance, and social assistance), and common rejection pitfalls. It helps authors refine general social science manuscripts to meet the rigorous academic standards of the journal.
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Sociological Theory and Social Structure Guide
sociological-studies
brycewang-stanford/Awesome-Journal-Skills
372
This guide provides deep insights into the requirements for publishing in top-tier sociological journals. It emphasizes shifting the focus from mere econometric policy evaluation or variable listing to profound sociological problem consciousness and theoretical dialogue. It guides authors on structuring articles that engage with core social mechanisms, whether using large-scale quantitative datasets or rich qualitative ethnographic material.
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