Software Documentation Issues Unveiled
Reviewed by Greg Wilson / 2021-10-06
One of the smartest things a mid-sized tech company can do is hire a librarian. You probably don't need one if you're two dozen people who all know each other and have at least a vague idea of what one another are doing, but by the time you have a hundred staff, someone needs to be responsible for figuring out how the wiki and Google Docs should be organized, what tags every repo should have, and so on. Without that, entropy slowly takes over and you spend an ever-increasing amount of time trying to find the design docs that you're sure someone wrote last year except maybe they were under their personal account and we no longer have access.
Aghajani2019 doesn't tackle this problem directly. Instead, it does the essential pre-work of taxonomizing the problems people have with software documentation by scraping data from GitHub issues, pull requests, mailing lists, and Stack Overflow. The result is the sort of evidence-based categorization that librarians (and the authors of linting tools) swoon over—you can click on the figure to get the full-sized version:
The full paper explains what each category and sub-category means, how common it is, and the evidence the authors have to justify its inclusion. As a bonus, they have made a replication package on GitHub if you'd like to explore their data yourself. It's the kind of quiet foundational contribution that our field needs more of, and I hope it will lead to tools that automatically warn developers about common problems.
For more on how to make things findable, please see Lin2020.
Aghajani2019 Emad Aghajani, Csaba Nagy, Olga Lucero Vega-Marquez, Mario Linares-Vasquez, Laura Moreno, Gabriele Bavota, and Michele Lanza: "Software Documentation Issues Unveiled". Proc. International Conference on Software Engineering (ICSE), 2019, 10.1109/icse.2019.00122.
(Good) Software documentation provides developers and users with a description of what a software system does, how it operates, and how it should be used. For example, technical documentation (e.g., an API reference guide) aids developers during evolution/maintenance activities, while a user manual explains how users are to interact with a system. Despite its intrinsic value, the creation and the maintenance of documentation is often neglected, negatively impacting its quality and usefulness, ultimately leading to a generally unfavourable take on documentation. Previous studies investigating documentation issues have been based on surveying developers, which naturally leads to a somewhat biased view of problems affecting documentation. We present a large scale empirical study, where we mined, analyzed, and categorized 878 documentation-related artifacts stemming from four different sources, namely mailing lists, Stack Overflow discussions, issue repositories, and pull requests. The result is a detailed taxonomy of documentation issues from which we infer a series of actionable proposals both for researchers and practitioners.