Reproducibility is the idea of being able to duplicate the results of a study or experiment. The reproducibility of code in the computational science field is very crucial in order to ease restrictions on collaboration and to prevent fraud results. In this literature review, I will be focusing on how the data collected from the 299 authors, who have published their articles in a computational physics journal, can help hypothesize the transparency of code and data. In order to do this, I will expand on previously collected publicly available demographic data such as Current Position, Institution, Affiliation, and Geography Information. I will then analyze the data by using R. I expect the results to show that authors who have had a longer tenure, are less transparent with their code and data. I also expect that an author’s country plays a significant role in the availability of code.
University of Illinois at Urbana-Champaign
Dr. Daniel Katz
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