AIRE 2023: 10th International Workshop on Artificial Intelligence and Requirements Engineering

2023 IEEE 31st International Requirements Engineering Conference Workshops (REW)(2023)

引用 0|浏览6
暂无评分
摘要
Requirements Engineering (RE) researchers have employed Artificial Intelligence (AI) techniques to tackle different notions of requirements quality, have applied the techniques to different case studies and domains, and have used different metrics to assess the performance of their techniques. Given the pervasiveness of AI-based systems in our daily life, recent years have also seen an increasing need for RE techniques to support sound and structured development of AI system, with particular interest in explainability of system behaviour. The primary purpose of the AIRE workshop is to explore synergies between AI and RE in order to identify complex RE problems that could benefit from the application of AI techniques and the other way round, thus addressing RE for AI challenges. The 2023 edition of the workshop received 14 submissions, which were independently reviewed by at least three program committee members. In the end, 9 papers were accepted. All the conflicts of interest were treated seriously and independently. The workshop takes place on September 5, 2023. We hope that you enjoy the AIRE'23 workshop and its proceedings. We believe that in the days when AI is gaining prominence in our daily lives, the RE community cannot neglect the benefits that AI techniques can deliver to the practice of requirements engineering. The workshop will feature a keynote by Dr. Alessio Ferrari from CNR-ISTI (Italy) on Artificial Intelligence in Engineering and Society: Blue Skies, Black Holes, and the Job of Requirements Engineers. We look forward to seeing you all at this workshop and the future editions. We are very grateful to the Program Committee members and authors of the submissions for their hard work and dedication in putting together this program. We would like to thank you all for your participation in AIRE'23.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要