DAC Paper Reproducibility

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Guides researchers in establishing credible, re-runnable experimental reproducibility for ACM/IEEE DAC electronic design automation manuscripts.

DAC Paper Reproducibility helps electronic design automation (EDA) researchers build airtight experimental credibility into their ACM/IEEE Design Automation Conference submissions. Because DAC lacks a formal artifact-badging track, reviewer confidence relies on strict provenance. This skill assists in pinning standard benchmark suites (ISPD, EPFL, ISCAS, CircuitNet), documenting open-source and commercial tool flows (OpenROAD, ABC, Yosys), reporting PDK and library versions, establishing seed and variance protocols for stochastic and ML-for-EDA methods, and managing double-blind to open-source repository transitions.

主な機能

01Pinning standard EDA benchmark suites, releases, and design splits
02Mapping paper claims directly to reproducible scripts and logs
03Structuring double-blind submission repositories and post-acceptance DOI archives
04Documenting full EDA toolchain versions and technology PDK libraries
051,074 GitHub stars
06Reporting seed, variance, and hardware specs for stochastic and ML flows

ユースケース

01Preparing experimental evaluation sections for DAC research paper submissions
02Documenting stochastic algorithms with multi-seed variance and hardware specifications
03Setting up anonymized review repositories and post-acceptance Zenodo archives