Computational · Paper · 2026

A template/ approach to Reproducible Generative Research: Architecture and Ergonomics from Configuration through Publication

Daniel Ari Friedman

Zenodo

Download PDF Publication source Paper folder on GitHub Read extracted text

Overview

The reproducibility crisis in computational research is fundamentally structural: research artifacts are scattered across disconnected tools. template/ applies Infrastructure as Code to the research lifecycle, making the manuscript, test suite, and provenance chain version-controlled, deterministically buildable, and independently verifiable.

reproducible researchinfrastructure as codebuild pipelineopen scienceModel Context Protocol

Overview source: Curated paper metadata.

Methods and contributions

Read the source for the full argument, qualifications, and evidence.

Findings and contributions

  • All three exemplar projects (39, 505 and 65 tests) completed the pipeline, a reported 100% success rate with zero mock violations.
  • Total pipeline duration across the three projects was ~125s on Apple M-series hardware, ~42s per project on average.
  • The infrastructure suite of ~3,083 tests reached 83%+ coverage against a 60% threshold, with zero mock violations.
  • The comparative feature analysis is reported to show template/ uniquely combining eleven distinctive capabilities in one enforced pipeline.
  • Among stated limitations, the provenance layer offers SHA-256 tamper detection but not cryptographic non-repudiation, since it lacks private-key signatures.

Methods

  • Two-Layer Architecture: 12 shared infrastructure subpackages + standalone projects — template/ separates a reusable infrastructure/ layer (~150 Python modules) from self-contained projects/ workspaces that consume it.
  • Eight-stage build pipeline from environment setup to LLM review — Stages run sequentially: setup, tests with coverage, analysis scripts, Pandoc/XeLaTeX rendering, hashing/watermarking, PDF validation, LLM review.
  • Zero-Mock testing policy with 90%/60% coverage gates — Tests use real filesystem operations and subprocesses instead of mocks, with coverage thresholds of 90% for projects and 60% for infrastructure.
  • SHA-256 hashing with steganographic watermarking for provenance — Rendered PDFs carry SHA-256 hashes in metadata plus alpha-channel overlays and QR codes for tamper detection.
  • Multi-project evaluation and feature comparison with peer tools — Three exemplar projects were run through the pipeline in a fast configuration that skips infrastructure tests and LLM review; template/ was also compared with peer tools on fourteen dimensions.

Summary sources: Paper metadata and evidence · Extracted source text.

PDF downloads

Archived files available directly from this site.

Citation

Citation metadata follows the unified bibliography.

Friedman, Daniel Ari. 2026. A template/ approach to Reproducible Generative Research: Architecture and Ergonomics from Configuration through Publication. Zenodo. DOI: 10.5281/zenodo.16903351. URL: https://doi.org/10.5281/zenodo.16903351.
Download bibliography

Catalog details and resources

Catalog row1
Citation keyFriedman2026TemplateApproachReproducibleGenerative001
Platform availability

Related in Computational

Other catalogued works in the same domain.

View all Computational works, software & media →