论文标题
使用神经关注和字节对编码的代码完成
Code Completion using Neural Attention and Byte Pair Encoding
论文作者
论文摘要
在本文中，我们的目标是基于Li et的神经网络进行代码完成。 Al ..我们的贡献是，我们使用的是字符和单词编码之间的编码，称为字节对编码（BPE）。我们在源代码文件上使用它，将其视为自然文本，而无需首先通过抽象语法树（AST）。我们已经实施了两个模型：注意力增强的LSTM和一个指针网络，最初引入了指针网络以解决词汇问题。我们有兴趣查看BPE是否可以替换对代码完成的指针网络的需求。
In this paper, we aim to do code completion based on implementing a Neural Network from Li et. al.. Our contribution is that we use an encoding that is in-between character and word encoding called Byte Pair Encoding (BPE). We use this on the source code files treating them as natural text without first going through the abstract syntax tree (AST). We have implemented two models: an attention-enhanced LSTM and a pointer network, where the pointer network was originally introduced to solve out of vocabulary problems. We are interested to see if BPE can replace the need for the pointer network for code completion.
