Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: JavaBERT: Training a transformer-based model for the Java programming
  language   Code quality is and will be a crucial factor while developing new software
code, requiring appropriate tools to ensure functional and reliable code.
Machine learning techniques are still rarely used for software engineering
tools, missing out the potential benefits of its application. Natural language
processing has shown the potential to process text data regarding a variety of
tasks. We argue, that such models can also show similar benefits for software
code processing. In this paper, we investigate how models used for natural
language processing can be trained upon software code. We introduce a data
retrieval pipeline for software code and train a model upon Java software code.
The resulting model, JavaBERT, shows a high accuracy on the masked language
modeling task showing its potential for software engineering tools.

10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an