Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/128546
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Type: Conference paper
Title: Essential Sentences for Navigating Stack Overflow Answers
Author: Nadi, S.
Treude, C.
Citation: Proceedings of the 2020 IEEE 27th International Conference on Software Analysis, Evolution, and Reengineering, 2020 / pp.229-239
Publisher: IEEE
Publisher Place: online
Issue Date: 2020
ISBN: 9781728151434
ISSN: 1534-5351
Conference Name: IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) (18 Feb 2020 - 21 Feb 2020 : London, ON, Canada)
Statement of
Responsibility: 
Sarah Nadi, Christoph Treude
Abstract: Stack Overflow (SO) has become an essential resource for software development. Despite its success and prevalence, navigating SO remains a challenge. Ideally, SO users could benefit from highlighted navigational cues that help them decide if an answer is relevant to their task and context. Such navigational cues could be in the form of essential sentences that help the searcher decide whether they want to read the answer or skip over it. In this paper, we compare four potential approaches for identifying essential sentences. We adopt two existing approaches and develop two new approaches based on the idea that contextual information in a sentence (e.g., “if using windows”) could help identify essential sentences. We compare the four techniques using a survey of 43 participants. Our participants indicate that it is not always easy to figure out what the best solution for their specific problem is, given the options, and that they would indeed like to easily spot contextual information that may narrow down the search. Our quantitative comparison of the techniques shows that there is no single technique sufficient for identifying essential sentences that can serve as navigational cues, while our qualitative analysis shows that participants valued explanations and specific conditions, and did not value filler sentences or speculations. Our work sheds light on the importance of navigational cues, and our findings can be used to guide future research to find the best combination of techniques to identify such cues.
Keywords: Internet; question answering (information retrieval); software engineering; text analysis; Web sites
Rights: © 2020 IEEE
RMID: 1000021079
DOI: 10.1109/SANER48275.2020.9054828
Grant ID: http://purl.org/au-research/grants/arc/DE180100153
Appears in Collections:Computer Science publications

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