Understanding Documentation Use Through Log Analysis: A Case Study of Four Cloud Services

要旨

Almost no modern software system is written from scratch, and developers are required to effectively learn to use third-party libraries and software services. Thus, many practitioners and researchers have looked for ways to create effective documentation that supports developers' learning. However, few efforts have focused on how people actually use the documentation. In this paper, we report on an exploratory, multi-phase, mixed methods empirical study of documentation page-view logs from four cloud-based industrial services. By analyzing page-view logs for over 100,000 users, we find diverse patterns of documentation page visits. Moreover, we show statistically that which documentation pages people visit often correlates with user characteristics such as past experience with the specific product, on the one hand, and with future adoption of the API on the other hand. We discuss the implications of these results on documentation design and propose documentation page-view log analysis as a feasible technique for design audits of documentation, from ones written for software developers to ones designed to support end users (e.g., Adobe Photoshop).

著者
Daye Nam
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Andrew Macvean
Google, Seattle, Washington, United States
Brad A. Myers
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Bogdan Vasilescu
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
論文URL

https://doi.org/10.1145/3613904.3642721

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Supporting Programmers and Learners B

310 Lili'u Theater
5 件の発表
2024-05-15 18:00:00
2024-05-15 19:20:00