MSR 2023
Dates to be announced Melbourne, Australia
co-located with ICSE 2023
Mon 15 May 2023 11:50 - 12:02 at Meeting Room 109 - Documentation + Q&A I Chair(s): Ahmad Abdellatif

The documentation of software libraries is an essential resource for learning how to use the library. Bad documentation may demotivate a developer from using the library or may result in incorrect usage of the library. Therefore, as developers select which libraries to use and learn, it would be beneficial to know the quality of the available documentation. In this paper, we follow a systematic process to create an automatic documentation quality evaluation tool. We identify several documentation quality aspects from the literature and design metrics that measure these aspects. We design a documentation quality overview visualization to visualize and present these metrics, and receive intermediate feedback through a focused interview study. Based on the received feedback, we implement a web service that can evaluate a given documentation page for Java, JavaScript, and Python libraries.We use this web service to conduct a survey with 26 developers where we evaluate the usefulness of our metrics as well as whether they reflect developers’ experiences when using this library. Our results show that participants rated most of our metrics highly, with Text Readability, and Code Readability (of examples) receiving the highest ratings. We also found several libraries where our evaluation reflected developers’ experiences using the library, indicating the accuracy of our metrics.

Mon 15 May

Displayed time zone: Hobart change

11:50 - 12:35
Documentation + Q&A IData and Tool Showcase Track / Technical Papers at Meeting Room 109
Chair(s): Ahmad Abdellatif Concordia University
Evaluating Software Documentation Quality
Technical Papers
Henry Tang University of Alberta, Sarah Nadi University of Alberta
What Do Users Ask in Open-Source AI Repositories? An Empirical Study of GitHub Issues
Technical Papers
Zhou Yang Singapore Management University, Chenyu Wang Singapore Management University, Jieke SHI Singapore Management University, Thong Hoang CSIRO's Data61, Pavneet Singh Kochhar Microsoft, Qinghua Lu CSIRO’s Data61, Zhenchang Xing , David Lo Singapore Management University
PICASO: Enhancing API Recommendations with Relevant Stack Overflow Posts
Technical Papers
Ivana Clairine Irsan Singapore Management University, Ting Zhang Singapore Management University, Ferdian Thung Singapore Management University, Kisub Kim Singapore Management University, David Lo Singapore Management University
GIRT-Data: Sampling GitHub Issue Report Templates
Data and Tool Showcase Track
Nafiseh Nikehgbal Sharif University of Technology, Amir Hossein Kargaran LMU Munich, Abbas Heydarnoori Bowling Green State University, Hinrich Schütze LMU Munich