Re-run, Repeat, Reproduce, Reuse, Replicate: Transforming Code into Scientific Contributions
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Abstract (arXiv)
Scientific code is not production software. Scientific code participates in the evaluation of a scientific hypothesis. This imposes specific constraints on the code that are often overlooked in practice. We articulate, with a small example, five characteristics that a scientific code in computational science should possess: re-runnable, repeatable, reproducible, reusable and replicable.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Aug 2017.
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025Reusability in MLOps: Leveraging Ports and Adapters to Build a Microservices Architecture for the Maritime Domaincited by 0
- 2025SymSeqBench: a unified framework for the generation and analysis of rule-based symbolic sequences and datasetscited by 0
- 2026AutoSG: LLM-Driven Solver Generation Solely from Task Prompts for Expensive Optimizationcited by 0
- 2026AutoSG: LLM-Driven Solver Generation Solely from Task Prompts for Expensive Optimization25 May 2026
- 2025SymSeqBench: a unified framework for the generation and analysis of rule-based symbolic sequences and datasets31 Dec 2025
- 2025Reusability in MLOps: Leveraging Ports and Adapters to Build a Microservices Architecture for the Maritime Domain9 Dec 2025