Day 1: Probability & Programming Workshop
At the Principles of Programming Languages (POPL) conference in January 2018, Facebook launched the Probability and Programming request for proposals addressing fundamental problems at the intersection of machine learning, programming languages, and software engineering, including differentiable programming, probabilistic programming, languages and tools for data science, programming tools built using “big code,” and applications of machine learning to optimize systems and human workflows.
We received 66 high-quality submissions, from which a selection committee composed of programming language experts throughout Facebook Research chose 10 winners. The RFP Awards track will highlight the work of these researchers and provide an opportunity for cross-pollination of ideas across the topics of the RFP.
Day 2: BIG CODE
Past few years have seen tremendous interest, both in academia and industry, in applying techniques from machine learning to building innovative developer tools. The Facebook "Big Code" Summit (FBCS) is a cross-industry conference for researchers and practitioners working in this exciting area. With one day of social interactions and technical talks about machine learning, programming languages, and software engineering, FBCS is the event to learn, exchange ideas and interact with like-minded geeks!
Day 3:PLEMM
Programming Language Enthusiasts Mind Melt (PLEMM) is a cross-industry conference for programming language designers and implementers. in the spirit of Microsoft’s Lang .NEXT and Oracle’s JVM Language Summit. One day of social interactions and technical talks about programming language from across the industry and academia, PLEMM is the event to learn, exchange ideas, and interact with like-minded programming language, compiler, and virtual machine geeks.
Day 1: Probability & Programming Workshop
8:30am - Breakfast
9:30am - Welcome/Intros/Agenda by Erik Meijer
10:00am-11:45am - Topic: Probabilistic Programming Language
10:00am - Opening up the black box of Probabilistic Program Inference (Todd Millstein, UCLA)
10:30am - A Probabilistic Domain-Specific Language for Common-Sense Data Cleaning (Alex Lew, MIT)
11:00am - Scalable Variational Inference for Probabilistic Programs (Erik B. Sudderth, UCI)
11:30am- Q&A
12pm - Lunch
1:15pm-2:00pm - Topic: Differentiable Programming Languages
1:15pm - Programs as Differentiable Data Objects (Thomas W. Reps and Jordan Henkel, University of Wisconsin-Madison)
2:00pm-5:30pm - Topic: Big Code
2:00pm - Zipper Code Embeddings (Aws Albarghouthi, UW)
2:45pm - Contextual Ensemble Learning for Software Productivity and Reliability (Lin Tan, Purdue University)
3:30pm - Break
4:00pm-CODA Deep RL Framework for Code Assistant (Mayur Naik, University of Pennsylvania)
4:45pm - Code Embeddings for Bug Finding (Aditya Thakur and Cindy Rubio Gonzàlez, UC Davis)
5:30pm - Wrap up/final thoughts
5:35pm - Break before dinner
6:00pm - Dinner
Day 2: Big Code Summit
8:30am - Breakfast
9:30am - Eran Yahav: Adversarial Examples for Models of Code
10:15am –Marc Brockschmidt: Program Representations for Deep Learning
11:00am - Break
11:30am - Nachi Nagappan: Data + Software Engineering: Better Together!
12:15pm - Vijay Murali: ML and IR for Scalable Crash Resolution
1:00pm - Lunch
2:00pm - Baisakhi Ray: Improving Software Reliability using Machine Learning
2:45pm - Ciera Jaspan: Improving Engineering Productivity at Scale
3:30pm - Break
4:00pm - Rishabh Singh: Neural Program Testing
4:45pm - Ayman Nadeem: GitHub Semantic Language Support Improvements
5:30 pm - Closing remarks (Satish Chandra)
5:45 pm - Happy hour/Dinner
Day 3: PLEMM
8:30am - Breakfast
9:30am - Emina Torlak: Solver-Aided Programming for All
10:15am - John Regehr: Building Compilers Using Data and Formal Methods
11:00am - Break
11:30am - Cristina Cifuentes: What is a Secure Programming Language?
12:15pm - Kotsya Serebryany
1:00pm - Lunch
2:00pm - Amanda Silver: Visual Studio IntelliCode: Lessons learned in infusing intelligence into popular programming environments
2:45pm - Phil Pizlo: IsoHeaps - fixing use-after-free by giving each type its own heap
3:30pm - Break
4:00pm - Mary Hall: Leveraging the Overlapping Goals of Compilers for High-Performance Computing and Deep Learning
4:45pm - David Kanter
5:30pm- Wrap up/final thoughts (Erik Meijer)
5:45pm - Happy hour