Machine Learning for Programming

18–19 July 2018, Oxford, UK

Workshop affiliated to CAV 2018, as part of FLoC 2018.

The two-day event will feature invited and contributed talks on improving software reliability and developer productivity by using machine learning, including deep learning. The techniques of interest include leveraging big code repositories (such as GitHub) to build models of code and using them for program analysis, synthesis, and repair techniques that advance the state of the art.

How to register?

Visit the FLoC registration page, select “Workshops only” (unless you also want to attend CAV or other FLoC events), fill in some details, and select two daily tickets for July 18th and July 19th.

Invited speakers

• Liam Atkinson, Prodo.AI
• Miltos Allamanis, Microsoft Research
• Earl Barr, University College London
• Swarat Chaudhuri, Rice
• Prem Devanbu, UC Davis
• Pushmeet Kohli, DeepMind
• Michael Pradel, TU Darmstadt
• Rishabh Singh, Google Brain
• Danny Tarlow, Google Brain
• Eran Yahav, Technion
• Martin Vechev, ETH Zurich
• Jules Villard, Facebook

Programme

https://easychair.org/smart-program/FLoC2018/MLP-program.html

Call for papers

Topics

The workshop accepts submissions of extended abstracts that will be disseminated on the workshop web site. We welcome applied and theoretical contributions exploring, among others:

• new learning algorithms, models, and architectures for the domain of programs;
• machine learning methods for program suggestion, synthesis, debugging, and other programming tasks;
• probabilistic extensions of conventional program analyses;
• source code representations for learning;
• applying natural language processing techniques to code, comments, documentation, and other software artifacts;
• description and evaluations of new tools.

Format

The accepted extended abstracts will not preclude subsequent publication in conferences or journals. Submitted papers should be most 5 pages in length (excluding references and appendices) and be prepared using the EPTCS style file. We will consider original research contributions as well well-prepared surveys and vision statements.

Each accepted extended abstract must be presented by an author at the workshop, 18-19 July 2018.

Submission site

https://easychair.org/conferences/?conf=mlp2018

Dates

• Extended abstract submission deadline: 15 April 2018
• Paper revisions accepted until: 30 April 2018
• Acceptance Notification: 15 May 2018
• Workshop: 18–19 July 2018

Program Committee

• Marc Brockshmidt, Microsoft Research
• Aditya Kanade, IISc Bangalore
• Viktor Kuncak (co-chair), EPFL
• Bruno Marnette (co-chair), Prodo.AI
• Sebastian Riedel, University College London
• Charles Sutton (co-chair), University of Edinburgh
• Luke Zettlemoyer, University of Washington

Student Grants

We have dedicated some budget to cover a limited number of student workshop tickets (and contribute towards travel and accommodation). If you are an MSc student, PhD student or junior Post Doc interested to apply, please contact sara@prodo.ai before June 19th with (1) a brief bio, (2) motivations to attend, and a (3) short list of references. We plan to get back to every candidate on June 20th.

Sponsors