From Programs to Deep Models – Part 3: Code Completion
This post discusses the task of automatic code completion through the application of deep learning methods.
This post discusses the task of automatic code completion through the application of deep learning methods.
We discuss the emerging problem of automatically synthesizing neurosymbolic programs, or programs that blend together neural networks and high-level code.
Working through a programming exercise, we see that Lisp’s “Code is data” philosophy is a natural enabler for program synthesis.
POPL is the premiere conference on the theoretical foundations of programming languages. The PC Chair, General Chair, and Steering Committee Chair of POPL 2020 review this year’s event.
As quantum computers become more practical, there is a rich opportunity to advance the development of tools to assist in the process of programming them, both now and in the future. To encourage more PL-minded researchers to work in this exciting new area, we established the Workshop on Programming Languages for Quantum Computing (PLanQC).