Assessing the generalizability of code2vec token embeddings

• Main Authors: KANG, Hong Jin, BISSYANDE, Tegawende F., LO, David
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Code Embeddings; Distributed Representations; Big Code; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4493; https://ink.library.smu.edu.sg/context/sis_research/article/5496/viewcontent/ase19_code2vec.pdf
• Institution: Singapore Management University

Many Natural Language Processing (NLP) tasks, such as sentiment analysis or syntactic parsing, have benefited from the development of word embedding models. In particular, regardless of the training algorithms, the learned embeddings have often been shown to be generalizable to different NLP tasks....