[AIRG] code2vec, 9/12

[JINMAN ZHAO <jzhao237@xxxxxxxx>]

Hi all,

Next Wednesday 9/12, we will discuss a recent work, code2vec, on generating embeddings for code.

The purpose of an embedding is to map symbolic entities into vector space while still preserving the relations between them in terms of distance. It can be viewed as a feature extraction process and is often the first layer for a deep learning model which works with symbolic inputs. The authors introduce the idea of viewing source code as bags of abstract syntax tree paths, and use them to better generate method or token embeddings, and also predict method names. In another closely related work [2] by the same authors, they use the same representation to predict variable types and other ML tasks over source code in Java, Python and _javascript_.

Time: 4pm, Wednesday, September 12

Location: CS 3310

Presenter: Jinman Zhao (jz@xxxxxxxxxxx)

Paper:

[1] code2vec: Learning Distributed Representations of Code

Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav

FloC 2018 Machine Learning for Programming

https://arxiv.org/abs/1803.09473

Related paper (in case you want to go deeper):

[2] A General Path-Based Representation for Predicting Program Properties

Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav

PLDI 2018

https://arxiv.org/abs/1803.09544

Hope to see you there!

Jinman Zhao