An essential part of research and scientific communication is researchers' ability to reproduce the results of others. While there have been increasing standards for authors to make data and code available, many of these files are hard to re-execute in practice, leading to a lack of research reproducibility. This poses a major problem for students and researchers in the same field who cannot leverage the previously published findings for study or further inquiry. To address this, we propose an open-source platform named RE3 that helps improve the reproducibility and readability of research projects involving R code. Our platform incorporates assessing code readability with a machine learning model trained on a code readability survey and an automatic containerization service that executes code files and warns users of reproducibility errors. This process helps ensure the reproducibility and readability of projects and therefore fast-track their verification and reuse.

翻译：研究和科学交流的一个重要部分是研究人员复制其他研究成果的能力。虽然作者提供数据和代码的标准越来越高,但其中许多档案难以在实践中重新执行,导致缺乏研究可复制性,这对同一领域的学生和研究人员来说是一个重大问题,他们无法利用以前公布的研究结果进行研究或进一步调查。为了解决这一问题,我们提议建立一个名为RE3的开放源平台,帮助改进涉及R代码的研究项目的可复制性和可读性。我们的平台包含评估代码的可读性,并有一个经过有关代码可读性调查培训的机器学习模型和一个自动集装箱化服务,执行代码文档,警告用户可复制错误。这一过程有助于确保项目的可复制性和可读性,从而加快项目核查和再利用。