To Search or To Gen? Exploring the Synergy between Generative AI and Web Search in Programming

被引:0
|
作者
Yen, Ryan [1 ]
Sultanum, Nicole [2 ]
Zhao, Jian [1 ]
机构
[1] Univ Waterloo, Waterloo, ON, Canada
[2] Tableau Res, Seattle, WA USA
基金
加拿大自然科学与工程研究理事会;
关键词
generative AI; code generation; LLM; web search; information foraging; sensemaking; cognitive science; INFORMATION;
D O I
10.1145/3613905.3650867
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The convergence of generative AI and web search is reshaping problem-solving for programmers. However, the lack of understanding regarding their interplay in the information-seeking process often leads programmers to perceive them as alternatives rather than complementary tools. To analyze this interaction and explore their synergy, we conducted an interview study with eight experienced programmers. Drawing from the results and literature, we have identified three major challenges and proposed three decision-making stages, each with its own relevant factors. Additionally, we present a comprehensive process model that captures programmers' interaction patterns. This model encompasses decision-making stages, the information-foraging loop, and cognitive activities during system interaction, offering a holistic framework to comprehend and optimize the use of these convergent tools in programming.
引用
收藏
页数:8
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