  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. 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 was
actively maintained at the time the data for this paper was collected, supports
the publication of executable code and data, is connected to the scholarly
publication process. By investigating the software documentation and published
articles, we compared the applications across 19 criteria, e.g. features that
support authors in creating and readers in studying executable papers. 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. 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.
