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Making simulation results reproducible-Survey, guidelines, and examples based on Gradle and Docker
Wilfried Elmenreich1, Philipp Moll1, Sebastian Theuermann1
1Universität Klagenfurt, Klagenfurt, Austria.
Peerj. Computer Science
|April 5, 2021
Summary
Researchers need open, accessible results for easier experiment reproduction. This study offers guidelines and evaluates software tools to improve research reproducibility in computer science, though no single solution is perfect.
Area of Science:
- Computer Science
- Research Methodology
Background:
- Reproducibility is a critical challenge in computer science research.
- Existing methods for ensuring reproducible research are often insufficient or difficult to implement.
Purpose of the Study:
- To survey researchers on their needs and challenges regarding reproducibility.
- To develop guidelines for enhancing research reproducibility.
- To evaluate software tools that can improve the reproducibility of research results.
Main Methods:
- Conducted a survey of researchers in academic and private sectors on reproducibility.
- Formulated guidelines based on survey findings.
- Analyzed and evaluated four software tool approaches for reproducibility.
- Investigated three specific software tools using actual research projects.
Main Results:
- Survey highlights a strong demand for open, accessible results and minimal effort for experiment reproduction.
- Evaluated software tools effectively enhance the reproducibility of simulation results.
- No single evaluated tool perfectly addresses all conflicting requirements for optimal reproducibility.
Conclusions:
- Guidelines and software tools can significantly improve research reproducibility in computer science.
- Further development is needed to create comprehensive solutions that meet all reproducibility requirements.
- Promoting open access and user-friendly tools is key to advancing reproducible research practices.
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