Skill UI

A comprehensive guide to adhering to ASA/ASR data-sharing and transparency standards for social science research. It helps users prepare thorough documentation, define data provenance (codebooks, scripts), manage confidentiality constraints (IRB, proprietary data), and ethically prepare materials for academic publication. Use this when structuring a manuscript's data section or anticipating reviewer questions about data verification.

This guide outlines the comprehensive process for submitting and evaluating Computer Aided Verification (CAV) research artifacts. It details the criteria for earning three badges (Available, Functional, Reusable), the two-phase review structure (smoke-test and full review), and best practices for packaging scientific tools, including the use of containers, pinned benchmarks, resource limits, and proof witnesses. This ensures reproducibility and rigor in academic research.

This guide outlines best practices for designing and executing Computer Aided Verification (CAV) empirical evaluations. It emphasizes ensuring evidence matches claims by using standard, pinned benchmark sets, selecting fair baselines, respecting equal resource limits, and employing rigorous reporting methods like cactus and scatter plots to establish technical soundness and performance.

Provides detailed guidelines for authors on how to accurately position their research novelty within the complex landscape of formal verification techniques, tools, and academic literature. It emphasizes shifting from a simple citation catalog to a 'delta-first' contrast, clearly articulating technical differences, crediting specific tool and benchmark lineages, and understanding the scope of related venues (e.g., CAV, TACAS, FMCAD).

This guide provides detailed protocols for achieving high levels of reproducibility in Computer Aided Verification (CAV) research. It emphasizes the necessity of pinning benchmark sets, recording exact tool versions, documenting resource limits (time/memory), and providing checkable proof witnesses to ensure that evaluation claims can be independently validated by competitors or reviewers.

Provides strict guidelines for assembling supplementary material for Computer Aided Verification (CAV) papers. It details how to separate decision-critical content (main theorems, proof ideas) into the primary body, while moving voluminous details (full proofs, massive benchmarks) to the optional appendix or artifact, ensuring the paper remains judgeable from the main text alone.

Use this comprehensive guide to manage the entire project lifecycle for a CAV (Computer Aided Verification) paper submission. It provides a backward-planning timeline, covering topics from initial concept fitting and evidence locking to the two-stage review process, optional artifact evaluation, and final camera-ready submission. Essential for managing technical academic deadlines and mitigating common failure modes.

This detailed guide outlines the structure and scientific rigor required for publishing high-quality papers in the domain of Computer Aided Verification (CAV). It instructs authors to transition their work from mere system demonstrations or benchmark reports to formally guaranteed, mathematically precise contributions, emphasizing clear scope definition, stated theorems, and proof ideas.

This comprehensive preflight checklist is designed for authors submitting manuscripts to top-tier academic journals. It guides users through critical compliance areas, including formatting adherence, double-blind anonymization techniques, reference management, word count verification, and the preparation of necessary supplementary files (e.g., funding acknowledgments). Use it to ensure your paper meets the rigorous standards of professional academic publishing.

This guide provides best practices for structuring complex academic manuscripts, particularly for conferences requiring a single-PDF submission model. It details how to optimally split content between the limited body (e.g., 12 pages) and the extensive appendix, ensuring that the crucial theorems, proofs, and auxiliary lemmas are presented in a verifiable and highly readable manner for peer reviewers. Key techniques include implementing restatement discipline and writing roadmap paragraphs for clear verification paths.

A comprehensive project management framework for authors submitting theoretical papers to major conferences (e.g., COLT). This guide outlines the entire lifecycle, emphasizing backward planning from the deadline, milestone setting (Result Freeze, Verification Pass), and critical quality checks, including proof assembly, anonymity sweeps, and rebuttal response. It is designed to mitigate common academic writing risks and ensure a robust submission process.

This comprehensive guide provides a detailed, step-by-step checklist for authors preparing manuscripts for high-level academic journals, specifically modeled after the requirements of China Rural Economy. It covers all critical stages, including formatting standards, double-blinding rules, reference citation completeness, and rigorous empirical data verification, ensuring submissions meet professional scholarly standards.