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This guide details the process of achieving ACM badges (Available, Functional, Reproduced) for academic artifacts at SenSys. It emphasizes creating a hardware-optional evaluation path, allowing reviewers to verify results and functionality without access to the original testbed. Key steps include implementing graded replay tiers, documenting data provenance (energy, traces), and performing smoke-runs.

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.

A comprehensive guide for authors submitting to top systems conferences (e.g., SenSys, MobiCom). It details how to structure the Related Work section by sweeping multiple literature lanes (IoT, embedded AI, networking), proving citation venues, and most importantly, distinguishing your novel mechanism from the single nearest prior system with concrete, measurable differences. Essential for academic publication rigor.

This guide details the unique two-deadline review model of SenSys. It provides authors with a comprehensive roadmap for interpreting complex rejection outcomes, structuring substantive revisions, formulating effective responses to reviewers, and understanding critical systems review criteria, such as energy measurement and baseline fairness. Essential reading for systems researchers.

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 for submitting networking research artifacts for SIGCOMM conferences. It dictates how to package code, downscale topologies, substitute traces, and pin environments so that reviewers can independently verify and reproduce the paper's headline results, establishing verifiable scientific claims.

A comprehensive guide for designing and auditing high-stakes networking experiments, particularly for top-tier academic submissions like SIGCOMM. It outlines the 'evidence ladder' from microbenchmarks to live deployment, emphasizing the need to select robust baselines, report full performance distributions (percentiles and variance), and accurately map the mechanism's operational break points.

Provides a comprehensive guide on structuring the 'Related Work' section for top-tier computer graphics conferences like SIGGRAPH. It teaches authors how to position a new contribution based on 'capability delta' (what prior methods fail to do) rather than chronology, covering specialized technical lanes (rendering, geometry, AI for graphics) and managing complex academic attribution.

This comprehensive guide outlines best practices for designing data systems evaluations, ensuring results are robust, reproducible, and convincing to expert reviewers. It covers workload realism, baseline fairness, necessary ablation studies, and advanced metric visualization techniques (e.g., sweeping curves, failure analysis) required for top-tier data systems research.

A comprehensive guide for authors in data systems and related fields on achieving rigorous, verifiable reproducibility for academic papers. It mandates detailing the provenance of every claimed result by pinning five critical layers: code version, configuration parameters, dataset source, workload characteristics, and hardware specifications. Best practices include reporting distributions (e.g., percentiles, variance) and maintaining a detailed 'repro debt ledger' to withstand intense peer review.

A comprehensive guide for structuring and refining high-quality database systems research papers for top-tier conferences like SIGMOD. It covers essential components such as establishing a clear page-one contract, integrating running examples, scoping measured system claims, adopting third-person voice, and adhering to the 12-page ACM template structure for maximum technical impact.

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.