Erik Meijer of Facebook has agreed to speak at the workshop.

Software is eating the world, but ML is going to eat software

“Democratizing ML” is a hot topic these days - particularly in industry. Efficiency, composability and accessibility of machine learning technology are active areas of investment for many research and product groups. Unfortunately, while machine learning has the potential to fundamentally improve how software is constructed, opportunities to leverage machine learning to improve more conventional developer tools (languages, compilers, and IDEs for example) have largely gone untapped. At Facebook we want to seize this opportunity. Our Developer Infrastructure team is on a mission to fundamentally rethink and retool Facebook’s developer toolchain by applying machine learning at every layer in our stack. Our goal is to make our developers more productive, and our processes and infrastructure more efficient, by deeply integrating ML into our programming languages and developer tools (such as IDEs, version control, or continuous integration systems) in novel ways. This talk will detail the work our team has done to improve developer efficiency and resource utilization at Facebook - from updating the Hack programming language to support probabilistic programming techniques, to developing a new suite of AI-driven developer tools. I’ll describe the lessons we’ve learned along the way, as well as future opportunities we see to optimize or auto-tune other common pieces of developer infrastructure.

History of the PPS Workshop

While there have been a number of recent probabilistic programming meetings at Dagstuhl, NIPS, for the DARPA PPAML program, and elsewhere, many participants were interested in a deeper focus on semantics and other programming language issues. This lead to the formation of the PPS meeting colocated with POPL, which promotes the investigation of probabilistic programming from these PL perspectives, and exposes others in the PL community to probabilistic programming.

The first PPS workshop was held January 23, 2016 in St. Petersburg, FL, colocated with POPL and immediately before the DARPA PI meeting for the PPAML program:

The second PPS workshop was held January 17, 2017 in Paris, colocated with POPL, and sponsored by SIGPLAN and SIGLOG:

Each year has two chairs, one from the previous year, and the other of whom stays on for the next year. Other program committee members are different from the previous year, to promote a variety of perspectives on probabilistic programming.

Call for Extended Abstracts

PPS 2018: Probabilistic Programming Languages, Semantics, and Systems

Probabilistic programming is the idea of expressing probabilistic models and inference methods as programs, to ease use and reuse. The recent rise of practical implementations as well as research activity in probabilistic programming has renewed the need for semantics to help us share insights and innovations.

This workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of probabilistic programming languages, semantics, and systems. Topics include but are not limited to:

  • design of probabilistic programming languages;
  • inference algorithms for probabilistic programming languages;
  • semantics (axiomatic, operational, denotational, games, etc) and types for probabilistic programming;
  • efficient and correct implementation;
  • and last but not least, applications of probabilistic programming.

For a sense of the talks and posters in past years, see:


In the tradition of the previous meetings, we anticipate that work on semantic foundations of probabilistic programming will be at the core of PPS 2018, but we are explicitly broadening the scope of PPS to embrace all aspects of probabilistic programming languages.

We expect this workshop to be informal, and our goal is to foster collaboration and establish common ground. Thus, the proceedings will not be a formal or archival publication, and we expect to spend only a portion of the workshop day on traditional research talks. In line with the SIGPLAN Republication Policy, inclusion in our informal proceedings is not intended to preclude later formal publication. Nevertheless, as a concrete basis for fruitful discussions, we call for extended abstracts describing specific and ideally ongoing work on probabilistic programming languages, semantics, and systems.

In line with the SIGPLAN Republication Policy, inclusion in our informal proceedings is not intended to preclude later formal publication.

Extended abstracts are up to 2 pages in PDF format. Please submit them by October 17 using EasyChair at

Important dates and the Program Committee are listed elsewhere on this page.