The use of autonomous bots for automatic support in software development tasks is increasing. In the past, however, they were not always perceived positively and sometimes experienced a negative bias compared to their human counterparts. We conducted a qualitative study in which we deployed an autonomous refactoring bot for 41 days in a student software development project. In between and at the end, we conducted semi-structured interviews to find out how developers perceive the bot and whether they are more or less critical when reviewing the contributions of a bot compared to human contributions. Our findings show that the bot was perceived as a useful and unobtrusive contributor, and developers were no more critical of it than they were about their human colleagues, but only a few team members felt responsible for the bot.
Taxonomy of migration scenarios for Qiskit refactoring using LLMs
Universidad Nacional de La Plata, Facultad de Informática Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA), Argentina（拉普拉塔国立大学计算机学院高级信息技术研究与培训实验室，阿根廷）
本研究面向 Qiskit 版本迁移中的量子代码重构问题，比较专家与 LLM 构建的分类体系并整合为统一框架，以支持 AI 辅助迁移和自动化重构评估。
Leveraging LLMs, IDEs, and Semantic Embeddings for Automated Move Method Refactoring
University of Colorado（科罗拉多大学）；Tulane University（路易斯安那州立大学）；Amazon Web Services（亚马逊网络服务）；JetBrains Research（JetBrains研究）；NEC Corporation（日本电报电话公司）；NEC Laboratories America（日本电报电话美洲实验室）；University of Texas at Dallas（德克萨斯大学达拉斯分校）；Concordia University（康科迪亚大学）；University of Colorado, JetBrains Research（科罗拉多大学，JetBrains研究）
Streamlining Acceptance Test Generation for Mobile Applications Through Large Language Models: An Industrial Case Study
Critical TechWorks；Faculty of Engineering, University of Porto（波尔图大学工程学院）；LIACC , Faculty of Engineering, University of Porto（波尔图大学工程学院计算科学与人工智能中心）；INESC TEC , Faculty of Engineering, University of Porto（波尔图大学工程电信研究所）
