Skill UI

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.

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 guide details the structured process for preparing and evaluating research artifacts for major academic conferences like SOSP. It covers badge targeting (Functional, Reusable), cooperative evaluation expectations, and best practices for packaging system-level artifacts, including defining tiers (runnable, provided-hardware, documented-only) and conducting 'kick-the-tires' smoke tests.

A comprehensive methodology for rigorous scientific research in operating systems and complex systems. This guide details how to pin environments (OS, firmware, hardware), automate data capture, and script all figures to ensure that experimental results are auditable and fully reproducible, protecting findings against review challenges.

A comprehensive guide for authors submitting to high-impact scientific journals. It outlines the essential principles for structuring experiments and presenting evidence, emphasizing claims-evidence matching, fair benchmarking, differentiating result sources (simulation, hardware, theory), and ensuring statistical rigor. Covers best practices across computer science, control, communication, and microelectronics.

This guide assists researchers in determining the optimal venue for their formal verification project. It helps decide whether the work belongs at TACAS (ETAPS) or a sibling conference (like CAV or VMCAI), depending on the emphasis (tool vs. theory), and guides the selection among the four distinct contribution categories (Research, Tool, Case-study, Demonstration).

This comprehensive guide is designed to help authors assess the methodological and theoretical suitability of their manuscript for Transportation Research Part B. It emphasizes that the core contribution must be a generalizable method, model, or theorem (e.g., in traffic flow, network optimization, or choice modeling), rather than a simple applied case study. Use this tool for venue selection, manuscript re-framing, and ensuring rigorous analytical justification.

A comprehensive guide detailing how to package and present research artifacts—including code, hardware designs, and datasets—for major academic conferences. It outlines best practices for both initial review-time evidence and long-term public reuse, ensuring reproducibility and maximizing the chances of adoption by future builders.

A comprehensive guide for optimizing computer science manuscripts targeting the USENIX Annual Technical Conference (ATC). It covers core systems research fields (OS, networking, storage, security), defining the required evidence bar (built artifacts, clean evaluation), and re-framing the paper's contribution to align with top-tier systems venue expectations.