JCRD Reproducibility & Artifact Packaging

•
1.1k
•

Establishes rigorous experimental reproducibility frameworks and anonymous runnable artifacts for submissions to the Journal of Computer Research and Development.

Designed specifically for researchers preparing submissions for the Journal of Computer Research and Development (《计算机研究与发展》, JCRD), this skill helps authors build bulletproof reproducibility packages that withstand rigorous double-blind peer review. It guides users through environment dependency freezing, random seed and non-determinism management, dataset versioning, LLM API response caching, and consistent metric measurement protocols. It also structures end-to-end anonymous code repositories with clear execution scripts mapped directly to manuscript figures and tables, ensuring external reviewers can effortlessly reproduce core findings without author intervention.

Key Features

01Freezes software dependencies, hardware configurations, and OS specs for repeatable runtime environments
02Establishes random seed controls and non-determinism handling across single and multi-run experiments
03Structures anonymous runnable artifacts compliant with double-blind peer review requirements
04Caches LLM/API outputs and logs precise dataset timestamps to avoid sampling divergence
05Generates standardized README templates mapped directly to paper figures and tables
061,079 GitHub stars

Use Cases

01Preparing anonymous artifact repositories and one-click reproduction scripts for JCRD journal submissions
02Documenting baseline metrics, hardware environments, and LLM query caches in academic research papers
03Resolving reviewer critiques regarding experimental variance, random seeds, or reproducibility claims