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GeezerVison is showing ml4code.github.io — Resources on Machine Learning for Big Code and Naturalness · Machine Learning for Big Code and Naturalness

Contribute to ML4Code

Machine Learning for Big Code and Naturalness

Research on machine learning for source code.

Contact Miltos Allamanis about this survey or website. Made with Jekyll and Hyde.

Presentations and Relevant Introductory Material

  • Tutorial: An Introduction to Learning from Programs by Marc Brockschmidt in VMCAI Winter School 2019 [slides].
  • Tutorial: Modelling Natural Language, Programs, and their Intersection in NAACL HLT 2018, 1 June 2018, New Orleans, LA, USA [slides] [video]

Datasets

Some resources about Big Code and Naturalness can be found at learnbigcode.github.io. A list of datasets used in this area can be found at the appendix of the survey and at learnbigcode.github.io.

Courses

A few university courses are been taught covering aspects of machine learning for code, big code or naturalness of code. Below there are a few that have publicly available material.

  • Analyzing Software using Deep Learning in University of Stuttgart [videos]
  • Seminars on Applications of Deep Learning in Software Engineering and Programming Languages in U.C. Berkeley
  • Machine learning for programming in the University of Cambridge, UK
  • Deep Learning for Symbolic Reasoning in Purdue University
  • Machine Learning for Software Engineering in TU Delft

Please, feel free to submit a pull request to adding more links in this page.

Workshops and Other Academic Events

The last few years a few workshops have been organized in this area. Please, feel free to add any missing or future workshops here.

  • Deep Learning for Code April 29 2022, ICLR 2022, virtual
  • NLP4Prog Workshop 6 August 2021, ACL 2021, virtual
  • Workshop on Computer-Assisted Programming 12 December 2020, NeurIPS 2020, virtual
  • ML on Code devroom at FOSDEM19 2-3 February 2019, Brussels, EU [videos]
  • Machine Learning for Programming 18–19 July 2018, Oxford, UK [videos]
  • International Workshop on Machine Learning techniques for Programming Languages 16 - 21 July 2018 Amsterdam, Netherlands
  • Workshop on Machine Learning and Programming Languages in PLDI 18 - 22 June 2018, Philadelphia, PA, USA
  • Workshop on NLP for Software Engineering 4 February 2018, New Orleans, LA, USA
  • The 55th CREST Open Workshop - Bimodal Program Analysis 30-31 October 2017, London, UK
  • Workshop on NLP for Software Engineering 13 November 2016, Seattle, WA, USA
  • Programming with “Big Code” 15-18 November 2015, Dagstuhl, Germany

Courses on Important Relevant Background

  • Sofware Analysis at Univ. of Pennsylvania. It is a great introduction to Program Analysis [videos]
  • Program Analysis at University of Stuttgart [videos]
  • Applications of Data Science for Software Engineering 2020 at Eindhoven University of Technology.

Competitions

  • nlc2cmd in NeurIPS 2020 by Project CLAI. Starts July 2020.
  • CodeSearchNet Challenge: Evaluating the State of Semantic Code Search by Github. Starts Sep 2019.
  • CodRep 2019: Machine Learning on Source Code Competition by KTH. Starts on April 25th 2019.
  • CodRep 2018: Machine Learning on Source Code Competition by KTH. Starts on April 14th 2018.

Other Collections of Related Work

  • source{d} has collected a set of links and papers in the area. You can access the list here.
  • Autormated Program Repair has a curated list of pointers for helping newcomers to understan the field, maintained by Martin Monperrus.
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