作者: Johannes Bader , Sonia Seohyun Kim , Frank Sifei Luan , Satish Chandra , Erik Meijer
关键词: Natural language 、 Software engineering 、 Software artifacts 、 State (computer science) 、 Perspective (graphical) 、 Software 、 Software development process 、 Code (semiotics) 、 Computer science
摘要: We address the question: How can AI help software engineers better do their jobs and advance state of practice? Our perspective comes from building integrating AI-based techniques in Facebook’s developer infrastructure over past two years. In this article, we describe three productivity tools that have built learn patterns artifacts: code search using natural language, recommendation, automatic bug fixing. also present a broader picture how machine learning bring insights to virtually all stages lifecycle.