The demand for data science and data scientists is growing fast, and so is corresponding size and scope of the the problem. PL technology, notably program synthesis, can help.
The authors of POPL’s 2020 most influential paper reflect on the journey that produced their award winning research on program synthesis, and the impact the work has had on them, the research community, and society at large, ever since.
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.