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.
The wealth of code now available on-line is fertile ground to enable machine learning to be applied to programming tasks. This post is the second in a series on this topic, focusing on the tasks of semantically labeling and captioning code.
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).
The history of machine-checked proofs about programming languages offers valuable lessons for the future of programming languages research.
Will machine learning automate programming out of existence, as it is doing for many other professions?
Open Access publication models aim to make scientific results accessible to everyone. How will we pay for them?
An impressive number of transformations in both compilers and in ordinary programming are special cases of a transformation called “defunctionalization.” This post explains what it is and the many places it’s useful.
Ideas from PL research, such as functional combinators, behavioural types, and compiler correctness proofs, can be applied to distributed systems, facilitating their understanding, implementation, and formal verification.
We share the results of a DARPA ISAT study, I-USHER: Interfaces to Unlock the Specialized HardwarE Revolution, arguing for new hardware/software interfaces to enable the revolution promised by hardware specialization.
Runtime Support for Multicore Haskell (ICFP’09) was awarded the SIGPLAN ten-year most-influential paper award in 2019. In this blog post we reflect on the journey that led to the paper, and what has happened since.