Stichwörter: Background; The trend toward open science increases the pressure on authors to provide access to the source code and data they used to compute the results reported in their scientific papers; Since sharing materials reproducibly is challenging; several projects have developed solutions to support the release of executable analyses alongside articles; Methods; We reviewed 11 applications that can assist researchers in adhering to reproducibility principles; The applications were found through a literature search and interactions with the reproducible research community; An application was included in our analysis if it (i) was actively maintained at the time the data for this paper was collected; (ii) supports the publication of executable code and data; (iii) is connected to the scholarly publication process; By investigating the software documentation and published articles; we compared the applications across 19 criteria; such as deployment options and features that support authors in creating and readers in studying executable papers; Results; From the 11 applications; eight allow publishers to self-host the system for free; whereas three provide paid services; Authors can submit an executable analysis using Jupyter Notebooks or R Markdown documents (10 applications support these formats); All approaches provide features to assist readers in studying the materials; e.g; one-click reproducible results or tools for manipulating the analysis parameters; Six applications allow for modifying materials after publication; Conclusions; The applications support authors to publish reproducible research predominantly with literate programming; Concerning readers; most applications provide user interfaces to inspect and manipulate the computational analysis; The next step is to investigate the gaps identified in this review; such as the costs publishers have to expect when hosting an application; the consideration of sensitive data; and impacts on the review process