Investigating user perceptions of conversational agents for software-related exploratory web search
Investigating user perceptions of conversational agents for software-related exploratory web search
复制标题
调查用户对软件相关探索性网络搜索的对话代理的看法
DOI：
10.1145/3510455.3512778
复制
发表时间：
2022
期刊：
影响因子：
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通讯作者：
Pollock, Lori
中科院分区：
文献类型：
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作者：
Frazier, Matthew;Kumar, Shaayal;Damevski, Kostadin;Pollock, Lori
通过自然对话响应用户信息请求的对话代理有可能彻底改变我们在Web上获取新信息的方式（即，执行探索性Web搜索）。会话搜索代理的最新进展使用流行的Web搜索引擎作为后端和复杂的AI算法来维护上下文，自动生成搜索查询，并将结果汇总为话语。虽然在一般主题上显示出令人印象深刻的结果，但这种技术在软件工程中的潜力尚不清楚。在本文中，我们研究了会话搜索代理的潜力，以帮助软件开发人员获得新的知识。我们还获得了用户对最新一代此类系统（例如，Facebook的BlenderBot2）已经具备了为软件开发人员提供服务的能力。我们的研究表明，用户发现会话代理有助于获得有用的信息，软件相关的探索性搜索，但是，他们的看法也表明期望和当前最先进的工具，特别是在提供高质量的信息之间的差距很大。与会者的答复为今后的工作指明了方向。
Conversational agents that respond to user information requests through a natural conversation have the potential to revolutionize how we acquire new information on the Web (i.e., perform exploratory Web searches). Recent advances to conversational search agents use popular Web search engines as a back-end and sophisticated AI algorithms to maintain context, automatically generate search queries, and summarize results into utterances. While showing impressive results on general topics, the potential of this technology for software engineering is unclear.In this paper, we study the potential of conversational search agents to aid software developers as they acquire new knowledge. We also obtain user perceptions of how far the most recent generation of such systems (e.g., Facebook's BlenderBot2) has come in its ability to serve software developers. Our study indicates that users find conversational agents helpful in gaining useful information for software-related exploratory search; however, their perceptions also indicate a large gap between expectations and current state of the art tools, especially in providing high-quality information. Participant responses provide directions for future work.