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This guide provides rigorous structural and disciplinary rules for authors submitting mobile-systems research to highly competitive conferences like MobiSys. It emphasizes moving beyond mere superlatives, mandating that all claims must be substantiated by explicit measurements of latency, energy, memory, and thermal budgets on real devices. Learn how to structure the paper to survive deep technical and systems-level peer review.

This guide provides a comprehensive audit checklist for designing and evaluating sensor-based systems (SenSys). It mandates rigorous, real-world measurements across five core axes: energy efficiency, on-device latency distribution, ground truth accuracy, deployment realism, and embedded AI footprint. It ensures that research results are based on measured hardware performance, not simulations or idealized baselines.

This comprehensive guide outlines the strict criteria for submitting a paper to the SenSys conference after the 2026 merger. It clarifies that the core contribution must be a built, measured sensing or embedded system, demonstrating value based on physical resources like energy, memory, and latency on real hardware, rather than being a pure algorithm or networking mechanism.

A comprehensive guide detailing the required structure and technical rigor for writing papers in sensing and embedded systems (SenSys). It mandates replacing vague adjectives with concrete, measured metrics (e.g., energy in joules, latency in milliseconds) and structuring the argument around a clear 'pain $\to$ gap $\to$ mechanism $\to$ measured behavior' arc on the first page. Essential for academic researchers and engineers.

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 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.

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.

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.

This guide provides a rigorous methodology for achieving scientific reproducibility in technical and user experience papers (e.g., UIST). It details three essential 'ledgers': the Build Ledger (pinning software, hardware, and environment dependencies), the Measurement Ledger (defining precise protocols for metrics like latency and accuracy), and the Study Ledger (documenting human evaluation tasks). Following these protocols ensures that external researchers can accurately rebuild the artifact and validate reported results.

A comprehensive guide for creating the two required artifacts for a WACV paper: an anonymous package for double-blind review, and a public release post-acceptance. It emphasizes reproducing deployed system claims (latency, power, robustness) and maintaining consistency across revision rounds.