从RSSE到BotSE：15年后重新审视潜力与挑战
From RSSE to BotSE: Potentials and Challenges Revisited after 15 Years
AI总结：
本文回顾了软件工程推荐系统（RSSE）的成就，并对比新兴的软件工程机器人（BotSE），指出两者在情境感知、知识共享和需求交互场景中仍有待挖掘的潜力。
摘要：
推荐系统与机器人都应主动且智能地回答软件开发者或其他项目利益相关者的问题，以帮助他们更高效地完成任务。本文回顾了较为成熟的软件工程推荐系统（RSSE）领域所取得的成就，以及正在兴起的软件工程机器人（BotSE）领域。我们讨论了两者的异同，简要回顾了当前的技术发展水平，并重点指出了三个尚未充分挖掘潜力的领域：更具社会技术性的情境感知、在知识获取之外辅助知识共享，以及覆盖与需求和用户-开发者交互相关的重复性或激励性场景。
英文摘要：
Both recommender systems and bots should proactively and smartly answer the questions of software developers or other project stakeholders to assist them in performing their tasks more efficiently. This paper reflects on the achievements from the more mature area of Recommendation Systems in Software Engineering (RSSE) as well as the rising area of Bots in Software Engineering (BotSE). We discuss the similarities and differences, briefly review current state of the art, and highlight three particular areas, in which the full potential is yet to be tapped: a more socio-technical context awareness, assisting knowledge sharing in addition to knowledge access, as well as covering repetitive or stimulative scenarios related to requirements and user-developer interaction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
