# codenn

**Repository Path**: wxwxzhang/codenn

## Basic Information

- **Project Name**: codenn
- **Description**: Summarizing Source Code using a Neural Attention Model - CODENN
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-11-04
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README




**Run CODENN**

See details of CODENN in our paper

Summarizing Source Code using a Neural Attention Model (https://github.com/sriniiyer/codenn/blob/master/summarizing_source_code.pdf)

Requirements

* Torch (http://torch.ch/docs/getting-started.html)
* Cutorch
* antlr4 for parsing C# (pip install antlr4-python2-runtime)

Setup environment

`export PYTHONPATH=~/codenn/src/:~/codenn/src/sqlparse`
`export CODENN_DIR=~/codenn/`
`export CODENN_WORK=./workdir`

Build both csharp and sql datasets

Install modified sqlparse

`cd src/sqlparse/`
`sudo python setup.py install`

Build datasets

`cd src/model`
`./buildData.sh`

Train codenn models and predict on test set

`./run.sh {sql|csharp}`