Skill UI

This guide outlines the best practices for preparing system artifacts for academic evaluation, following the ACM Artifact Review and Badging scheme. It details how authors must ensure reproducibility, especially for tail latency and cost results, by providing scaled-down testbeds, comprehensive documentation, and clear provenance tracking to satisfy conference evaluators.

A comprehensive guide for drafting the critical author response (rebuttal) for the SoCC conference. Since there is no major revision round, this single, high-stakes turn must persuasively address concerns from both systems and data/measurement reviewers. It emphasizes correcting factual errors, supplying missing numbers (like tail latency and cost), and maintaining strict dual anonymity.

This comprehensive guide outlines the mandatory steps for transforming an accepted, anonymized academic paper into the final ACM Digital Library Camera-Ready format. It covers de-anonymization, adhering to ACM metadata standards (DOI, ORCID, CCS concepts), integrating reviewer feedback, and ensuring permanent reproducibility of code and traces.

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.

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.

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.

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.

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.

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.

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.

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.

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.