Not logged in.

Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title On the Helpfulness of Answering Developer Questions on Discord with Similar Conversations and Posts from the Past
Organization Unit
Authors
  • Alexander Lill
  • André Meyer
  • Thomas Fritz
Presentation Type paper
Item Subtype Original Work
Refereed No
Status Published electronically before print/final form (Epub ahead of print)
Language
  • English
Page Range Epub ahead of print
Event Title 46th International Conference on Software Engineering (ICSE 2024)
Event Type conference
Event Location Lisbon, Portugal
Event Start Date April 14 - 2024
Event End Date April 20 - 2024
Publisher ACM Digital library
Abstract Text A big part of software developers’ time is spent finding answers to their coding-task-related questions. To answer their questions, developers usually perform web searches, ask questions on Q&A websites, or, more recently, in chat communities. Yet, many of these questions have frequently already been answered in previous chat conversations or other online communities. Automatically identifying and then suggesting these previous answers to the askers could, thus, save time and effort. In an empirical analysis, we first explored the frequency of repeating questions on the Discord chat platform and assessed our approach to identify them automatically. The approach was then evaluated with real-world developers in a field experiment, through which we received 142 ratings on the helpfulness of the suggestions we provided to help answer 277 questions that developers posted in four Discord communities. We further collected qualitative feedback through 53 surveys and 10 follow-up interviews. We found that the suggestions were considered helpful in 40% of the cases, that suggesting Stack Overflow posts is more often considered helpful than past Discord conversations, and that developers have difficulties describing their problems as search queries and, thus, prefer describing them as natural language questions in online communities.
Free access at DOI
Digital Object Identifier 10.1145/3597503.3623341
Other Identification Number merlin-id:24070
PDF File Download from ZORA
Export BibTeX
EP3 XML (ZORA)
Keywords Developer Questions, Chat Community, Semantic Similarity