Although we have attempted to make our evaluation as objective as possible, subjective biases and preferences will usually influence choice of tooling (cf. the editor war). Additionally, our evaluation methods are informal to some extent, not strictly empirical, and non-reproducible. Nevertheless we feel that publishing them here may be useful to record the criteria we have taken into account.
Requirements for single tool documentation software (cf. documentation tooling section):
- (1) Sustainability
- (2) Single tool toolchain
- (3) Usability
- (3a) Human-readable source format
- (3b) Javadoc integration
- (3c) Continuous integration capabilities
- (3d) Maintainability
- (3e) Maintainability (dependencies)
- (3f) Usability of representations
- (4) Different representation forms
To evaluate which documentation tool may be the most suitable for our needs, we have marked it with a value from 1-5 for each requirement, with 1 being the lowest ("worst") mark and 5 the highest ("best").1
Table: Scores for the different requirements, cf. list above. x̄(3) is the mean of all Usability sub-requirements.
As of now, reliable measures for predicting the sustainability of a software do not exist , and intrinsically, the actual sustainability of a software can only be determined in hindsight. Therefore, assessing the sustainability potential for a software is a qualitative process, partly driven by the requirements of the project for which the software is assessed.
Despite this constraint, assumptions over the sustainability potential of a documentation software project can be based on some assessable factors, e.g., age of the software, approximated user base, development status, frequency of contributions, architecture, pervasiveness of a technological community, level of documentation, maturity of its dependencies, etc.
In the evaluation process, we have tried to approximate each candidate's potential for sustainability, which we present in the following. Additionally, we give the SourceRank metric for high quality packages used by libraries.io, based on the actual products we would employ.
 S. Druskat, 'A proposal for the measurement and documentation of research software sustainability in interactive metadata repositories', in Proceedings of the Fourth Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE4), University of Manchester, Manchester, UK, 2016 [Online]. Available: http://ceur-ws.org/Vol-1686/
Sphinx is a documentation generator written in Python. It is used to generate the documentation for the Python programming language itself as well as many large Python projects. The documentation platform Read the Docs uses Sphinx to automate the creation and deployment of software documentation.
We have rated the sustainability of Sphinx with rST as very high (5).
We have rated the sustainability of Sphinx with CM as medium (3) due to additionally required extensions and the non-standard use case which is not as well supported as the standard one using rST.
SourceRank metric for the Sphinx project: 23
Python, Sphinx' implementation language, is a highly used programming language, with an estimated 41% market share, as of 2019, and increasing interest as of June 2019. Sphinx has a high criticality due to its use as the Python language documentation platform, and its pervasiveness of the Python community, where it must be regarded as the default documentation tool. As of June 2019, Sphinx is used by over 57,000 projects on Github alone. The Sphinx hosting service Read the Docs has hosted around 100,000 projects in 2018 (including Sphinx and mkDocs projects). Sphinx is a mature project, with 126 releases, the first one from Mar 2008. It is also actively developed, with an average of around 3 commits per day, with the last 100 commits within the last 17 days at the time of writing, a contributor base of 422, of which 51 (12%) have actively contributed over the last year, and in this period, 45 contributors (11%) have made more than 1 commit. Sphinx has averages of 0.9 issues per day and 0.5 pull requests per day. Its 5 dependencies seem to be mature, based on the fact that they all have been released in major versions.
We have rated the sustainability of mdBook as high (4).
SourceRank metric: 15
Although Rust, mdBook's implementation language, is relatively young - development has started in 2006 - it is growing in popularity and sees increasing interest. Major software projects are written in Rust, such as the Quantum and Servo browser engines, developed by Mozilla and used in the Firefox web browser, Facebook's Libra cryptocurrency, Dropbox's file system, and security features in the Tor project. mdBook has a high criticality as the main documentation tool for the Rust language itself and its pervasiveness as the documentation tool for many Rust projects. mdBook is a relatively mature project, with 44 releases, the first one from Aug 2015. It is also actively developed, with an average of around 0.86 commits per day, with the last 100 commits within the last 96 days at the time of writing, a contributor base of 124, of which 43 (35%) have contributed over the last year, and in this period, 22 contributors (18%) have made more than 1 commit. mdBook has averages of 0.34 issues per day and 0.33 pull requests per day. Its 25 dependencies seem somewhat mature, with 13 of them having been released in major versions.
We have rated the sustainability of Jekyll as high (4).
SourceRank metric: 27
The popularity of Jekyll's implementation language, Ruby, seems to stagnate at around 9% market share and sees decreasing interest. Nevertheless, its market share has remained largely unchanged in the developer community over the last 6 years, and several large software projects are written in Ruby, including the Github development platform, Airbnb, Kickstarter, SlideShare. Jekyll has a high criticality as the main tool for generating Github pages. It is a mature project, with 136 releases, the first one from Dec 2008. Jekyll is also actively developed, with an average of around 2.7 commits per day, with the last 100 commits within the last 76 days at the time of writing. It has a contributor base of 852, of which 12 (1%) have contributed over the last year, and in this period, 7 contributors (<1%) have made more than 1 commit. Jekyll has averages of 1 issue per day and 0.9 pull requests per day. As of June 2019, Jekyll is used by over 296,000 projects on Github alone. Its 13 dependencies seem to be mostly mature, based on the fact that all but 2 have been released in major versions.
Asciidoctor is a processor and publishing toolchain for the AsciiDoc markup language. It is written in Ruby. Asciidoctor is used to build documentation for a number of larger software projects, including Grails, the Gradle build automation tool, Red Hat documentation, Solr, and many others.
We have rated the sustainability of Asciidoctor as medium (3).
SourceRank metric of the AsciiDoctor Maven plugin: 10
The popularity of Asciidoctor's implementation language, Ruby, seems to stagnate at around 9% market share and sees decreasing interest. Nevertheless, its market share has remained largely unchanged in the developer community over the last 6 years, and several large software projects are written in Ruby, including the Github development platform, Airbnb, Kickstarter, SlideShare. It is a mature project, with 60 releases, the first one from Feb 2014. Asciidoctor is actively developed, with an average of around 1.7 commits per day, with the last 100 commits within the last 82 days at the time of writing. It has a contributor base of 115, of which 21 (18%) have contributed over the last year, and in this period, 6 contributors (5%) have made more than 1 commit. Asciidoctor has averages of 0.8 issues per day and 0.5 pull requests per day. Its 3 dependencies seem to be immature, as none of them have a major release version.
mkDocs is a static site generator for project documentation. It is written in Python.
We have rated the sustainability of mkDocs as medium (3).
SourceRank metric: 9
Python, mkDocs' implementation language, is a highly used programming language, with an estimated 41% market share, as of 2019, and increasing interest as of June 2019. Its criticality seems to be low, as we could not find any large software projects documented with it. It is a mature project, with 41 releases, the first one from Jan 2014. mkDocs is actively developed, with an average of around 0.7 commits per day, with the last 100 commits within the last 444 days at the time of writing. It has a contributor base of 126, of which 27 (21%) have contributed over the last year, and in this period, 6 contributors (5%) have made more than 1 commit. mkDocs has averages of 0.6 issues per day and 0.4 pull requests per day. Its 7 dependencies seem to be mature, as 6 out of 7 have a major release version.
Assessing the usability of software is an opinionated process which takes into account encountered and predicted use in a specific context. In our evaluation, we have taken into account the readability of the source format, Javadoc integration, continuous integration capabilities, maintainability, maintainability of dependencies, and the usability of representations.
We have evaluated reStructuredText to be less-than-perfectly human-readable and human-usable due to
- its syntax for hyperlinks, which is not in-situ but instead uses an in-text underscore syntax
Text `link text_` textin combination with a text-external external footnote syntax
.. _link text: https://hyperlinkfor named links, which compares unfavourably with the Markdown format;
- the four-whitespace indentation convention for code blocks, which disallows easy copy and paste of valid source code snippets.
Sphinx (CM), mkDocs, mdBook, Jekyll
We have evaluated Markdown to be very human-readable and human-usable, independent of implementation dialects. Markdown does not exhibit the same syntax-specific issues as reStructuredText.
We have evaluated AsciiDoc, the input format for Asciidoctor, to be human-readable, despite some idiosyncrasies in the syntax, such as
<whitespace>+ for single line breaks, and the less graphic headline syntax.
We have eventually decided to disregard the integration of Javadoc API documentation as a deciding factor for the best-suited documentation tool for the project. Javadoc-based HTML generation has been a standard feature of Java and Maven for years, and linking from any running text documentation to the respective API documentation is trivial, and can be automated in continuous integration. Nevertheless we provide a quick overview of the evaluations here.
At the time of the evaluation, only Sphinx with reStructuredText offered a clear way to integrate Javadoc,
via the javasphinx extension.
This extension has since been deprecated, and therefore, the requirement is of no consequence for the
This is why all tools have been evaluated as not providing Javadoc integration with a score of
All evaluated tools can be automated via a continuous integration solution such as Travis CI (used in our project).
However, bespoke scripts have to be created (and maintained) to produce and deploy the respective HTML representations,
as none of the tools provide this functionality out-of-the-box.
Therefore, all tools have been evaluated with medium capabilities (
3), with the exception of Asciidoctor, for which a
Maven plugin exists, which you can read about on the Asciidoctor website. As Hexatomic uses Maven in the build process, this is helpful, and Asciidoctor has therefore been
evaluated with a score of
We have looked at the maintainability of the tools, and have mainly evaluated ease-of-installation and updates, and dependencies.
Sphinx with rST and mkDocs are installable and updatable via standard Python technologies, i.e., an installation of Python and
mdBook is provided as a binary, which can be downloaded and used as is; alternatively, the standard way to install Rust software also works, i.e., via a Rust and
installation. All three tools are more or less self-contained to run required functionality such as tables of contents, search, etc., out-of-the-box, with existing modules for further
functionality, and have therefore been scored with
Asciidoctor requires an implementation of Ruby, and can be installed from an OS package manager or as a Ruby gem. It also requires extensions for
processing documentation sources, which has led to a lower evaluation at
Finally, Sphinx with CM has bee evaluated at
2, as it requires hacks to include directives in Markdown which are not natively supported, such
as the ones needed to create a table of concents. These leads to manual work which in turn needs to be standardized within the project, documented, and followed.
This leads to a loss of maintainability for Sphinx with CM.
Dependencies in our evaluation are additional software which has to be installed in order to use the respective tool in our project.
mdBook has fared best, as it did not need additional software that needed to be actively installed, although a large number of its runtime dependencies do not have
Jekyll has achieved the lowest score, as specific functionality required the inclusion of many plugins in the configuration file.
The other tools have received scores of
3, as they needed a modicum of configuration via extensions and/or had a larger number of runtime dependencies with non-major releases.
mkDocs and Jekyll have both received low scores in assessing the usability of their HTML outputs. mkDocs can handle multiple pages, and contains global search, but it generally does not provide many features. This includes a maximum navigation depth of 2, which is not sufficient for our use case. Jekyll does not provide search or tables of contents out-of-the-box, and has to be customized to achieve the required level of functionality. Asciidoctor provides no client-side search, and per default produces single pages only. Sphinx does provide access to different versions of the documentation, and provides multi-page functionality and tables of contents, but its search does not provide good results. mdBook provides good search, different themes per default, menu fold functionality, multiple pages and a table of contents, as well as forward and backward buttons, code copy, and single page prints which can also be used to generate PDFs.
Only Sphinx can comfortably handle a large number of different representations of documentations, such as LaTeX, EPub3, man pages, and more. The common PDF format has to be produced using an extension. mdBook uses a generic approach by providing a print button which compiles a single page view of the documentation. This can then be used to produce PDFs or other outputs via the browser's print dialogue. Asciidoctor has an external PDF converter, which, however, requires Ruby. It can produce manpages natively. Producing different presentations from Jekyll is cumbersome. PDFs can be produced via HTML to PDF conversion software, and a wrapper plugin for Jekyll exists. mkDocs does not support PDF conversion natively, although a plugin exists, which, however, relies on different other software which have to be installed separately.
To calculate a final score for each tool, we have calculated the mean for all usability sub-categories in (3), and have calculated the mean across the three values. The results are presented in the table below, and are also available as a Jupyter notebook.
Table: Scores for the different requirements, and final scores, cf. list above. x̄(3) is the mean of all Usability sub-requirements.
Due to the restrictions in usability (and slightly decreased human-readability) that reStructuredText represents (cf. section Human-readable source format), as well as a personal preference for markdown, we have decided to use mdBook for the text-based documentation of Hexatomic.
We use local installations of mdBook on development machines to write the user, the developer & maintainer, and this project documentation. We use the Travis CI continuous integration platform to produce the documentation representations, and deploy them to GitHub Pages.
The sources for the project website reside in a dedicated repository, github.com/hexatomic/hexatomic.github.io. The sources for the Hexatomic software are held in the development repository for Hexatomic, github.com/hexatomic/hexatomic.