Generating Clarifying Questions for Query Refinement in Source Code Search
Not on the map. Why?
Abstract (arXiv)
In source code search, a common information-seeking strategy involves providing a short initial query with a broad meaning, and then iteratively refining the query using terms gleaned from the results of subsequent searches. This strategy requires programmers to spend time reading search results that are irrelevant to their development needs. In contrast, when programmers seek information from other humans, they typically refine queries by asking and answering clarifying questions. Clarifying questions have been shown to benefit general-purpose search engines, but have not been examined in the context of code search. We present a method for generating natural-sounding clarifying questions using information extracted from function names and comments. Our method outperformed a keyword-based method for single-turn refinement in synthetic studies, and was associated with shorter search duration in human studies.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jan 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 0; 2024: 1.
2 papers.
- 2024A Survey of Conversational Searchcited by 22
- 2022Python Code Generation by Asking Clarification Questionscited by 16
- 2024A Survey of Conversational Search21 Oct 2024
- 2022Python Code Generation by Asking Clarification Questions19 Dec 2022