Skill UI

A detailed guide on how to structure and position the 'Related Work' section for high-stakes academic conferences like DAC, ICCAD, and DATE. It teaches authors to move beyond simple surveys and instead create a 'delta statement,' explicitly defining the limitations of prior art and quantifying the unique advances of the current work in terms of Quality of Results (QoR).

A comprehensive guide for establishing research reproducibility in Electronic Design Automation (EDA). It details best practices for pinning benchmark suites, disclosing specific tool versions (open/commercial), documenting technology nodes (PDKs), and handling stochastic data flows (seeds, variance). Essential for ensuring that semiconductor design claims and ML-for-EDA results are credible and verifiable by the academic community.

A detailed model of the ACM/IEEE Design Automation Conference (DAC) research manuscript review process. This guide explains the double-blind, TPC-driven, and single-shot nature of the evaluation, emphasizing the critical balance between genuine novelty and measured Quality-of-Results (QoR). It outlines the high standards for evidence fairness, benchmark credibility, and ablation studies required for acceptance, differentiating DAC's approach from architecture and software venues.

This comprehensive guide provides a detailed audit checklist for submitting research manuscripts to major design automation conferences (e.g., DAC). It covers critical steps such as the two-stage abstract/manuscript timeline, adherence to the strict 6+1 page format, ensuring double-blind anonymization (removing all identifying metadata), declaring TPC conflicts, and mitigating common submission risks. Essential reading for researchers preparing for high-stakes academic submissions.

This comprehensive guide assists researchers and practitioners in selecting the optimal venue and track (e.g., DAC, ICCAD, ISCA) for their electronic design automation (EDA) or chip-design project. It clarifies the critical distinction between the archival Research Manuscript track and the industry-facing Engineering Track at DAC, emphasizing the need to frame contributions using measurable Quality of Results (QoR) improvements, novel algorithms, or real-world industrial lessons.

This guide provides comprehensive standards for designing, auditing, and reporting empirical evaluations in database systems research. It emphasizes the principle that evidence must proportionally match the claim, requiring the use of real-world workloads, fair and tuned baselines, thorough measurement of variance and state (warm/cold), and fully reproducible evaluation harnesses. It also outlines the higher bar for 'Experiments & Analysis' papers.

This comprehensive guide serves as a venue selection and content re-framing tool for research at the intersection of energy and environmental science. It details the high quantitative standards, required evidence (e.g., LCA, full-cell data, techno-economic analysis), and specific scope areas (solar, batteries, CO₂ capture) expected by Energy & Environmental Science (EES). Use this before submission to ensure your manuscript meets EES's broad, interdisciplinary impact criteria.

This guide assists in structuring the design of Environmental Science & Technology (ES&T) studies, including lab, mesocosm, field sampling, or modeling experiments. It ensures methodological rigor by planning for environmental relevance, necessary controls (e.g., abiotic loss, sorption), proper replication, mass/energy balance, and a comprehensive QA/QC plan from the outset, helping the study withstand expert peer review.

A comprehensive framework for ensuring rigorous scientific reproducibility in systems papers. It details how to establish a full provenance ledger (tracking hardware, software commits, and workloads), manage performance variance through repeated runs and statistical reporting, and implement automated pipelines so that all reported figures can be regenerated from raw data.

This guide meticulously models the rigorous decision-making machinery of top-tier academic conferences, using EuroSys as a detailed example. It covers the two-round submission cycle, the 'Accept/Revise/Reject' outcome logic, double-blind review mechanics, and critical criteria (like deployment plausibility and verifiable fairness) that determine a paper's success. Ideal for researchers and graduate students preparing systems research submissions.

A comprehensive guide for drafting and revising top-tier systems papers, specifically for conferences like EuroSys. It details the required academic structure, including building the problem-to-mechanism arc, managing the 12-page technical budget, writing rigorous evaluation sections (including measuring failure cases), and maintaining the necessary double-blind academic voice.

This comprehensive guide outlines best practices for achieving rigorous scientific reproducibility, especially for research involving storage systems and hardware dependencies. It mandates documenting not only the code but also the specific device models, firmware versions, operating states, and full measurement protocols to ensure verifiable results by peer readers.