Cited by 174Software Engineering ResearchInformation Retrieval and Search BehaviorSoftware Engineering Techniques and Practices

What do developers search for on the web?

Open access
Xia, Xin, Bao, Lingfeng, Lo, David, Kochhar, Pavneet Singh, Hassan, Ahmed E., Xing, Zhenchang·2017·Empirical Software Engineering

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Crossref · 10.1007/s10664-017-9514-4

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  • LLM prompts can allow developers to provide more context, which can enable them to receive information that more precisely aligns with their specific needs, potentially reducing the time spent sifting through web information.

    “Compared to general web search queries [74], LLM prompts can allow developers to provide more context, which can enable them to receive information that more precisely aligns with their specific needs, potentially reducing the time spent on sifting through the information obtained from the web to suit their particular requirements.”

    From Using an LLM to Help With Code Understanding (2024) · cites this paper as [74]

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References 32 · Cited by 174

Authors
Xia, X., Bao, L., Lo, D., Kochhar, P. S., Hassan, A. E., & Xing, Z.
Affiliations
  • University of British Columbia (CA)
  • Zhejiang University (CN)
  • Singapore Management University (SG)
  • Queen's University (CA)
  • Australian National University (AU)
Corresponding author
Bao, Lingfeng
Venue
Empirical Software Engineering
Published
2017-04-09
Volume
22
Issue
6
Pages
3149-3185
ISSN
  • 1382-3256 (ISSN-L)
  • 1573-7616
OpenAlex
W2604794021
Cited by
174
References
32
Citations by year
2026: 8 · 2025: 16 · 2024: 17 · 2023: 21 · 2022: 27 · 2021: 32 · 2020: 18 · 2019: 19 · 2018: 15 · 2017: 1
FWCI
27.03
Type
journal article
Language
en
Open access
Locations
  • Empirical Software Engineering (publishedVersion)
  • ANU Open Research (Australian National University) (submittedVersion)
  • Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (submittedVersion, other-oa)
Funders
  • Baidu
  • National Natural Science Foundation of China
  • Ministry of Science and Technology of the People's Republic of China
Topics
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Research
  • Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
Keywords
search query analysis, debugging, code reuse, third-party libraries, code search engines, domain-specific search engines, search query generation, software productivity

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