Tools and techniques for computational reproducibility.

Area of Science:

• Computational science
• Scientific research methodology

Background:

• Scientific findings rely on documented research steps for verification and further development.
• Reproducibility ensures that research steps can be retraced to yield similar results.
• Computers are integral to research but introduce complexities in achieving reproducibility.

Purpose of the Study:

• To address challenges in computational reproducibility in scientific research.
• To present practical strategies for enhancing the reproducibility of research findings.
• To guide scientists in applying and combining different reproducibility techniques.

Main Methods:

• Review and description of seven distinct strategies for improving computational reproducibility.
• Analysis of the strengths and limitations of each strategy.
• Guidance on the applicability of each method in various scientific contexts.

Main Results:

• Computational findings often lack reproducibility due to software and documentation complexities.
• Seven strategies are detailed to overcome common reproducibility hurdles.
• Each strategy has specific applications, strengths, and limitations.

Conclusions:

• Improving computational reproducibility requires careful attention to software packaging, installation, and execution.
• A combination of strategies is often necessary to ensure robust reproducibility across different research scenarios.
• Adopting these strategies can enhance the reliability and verifiability of scientific research.