CodeErrorDetection

Investigating the use of a DL system for detecting errors in code.

Getting Started

Install Miniconda

Please follow these instructions to install Miniconda (Python 3.8).

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

Create and Activate a Conda Environment

The Conda environment used for the tutorial is specified in the environment.yml file. Creating the environment is a on-time operation:

cd CodeErrorDetection
conda env create -f environment.yml

You should close the terminal and open a new one to make sure that Conda is correctly setup in your environment.

In any new console, remember to activate the newly created environemnt:

conda activate codeErrorDetection

Here you can find more instructions on how to create and manage a Conda environment.

Run Data Generation

python generateData <filename.py>

Create Dataset and Validate

./validateAndCreateDataset.sh

Train Neural Network (various models in file to be selected from)

python train.py

Project Report

This powerpoint contains a summary of different ideas investigated and explored along with work and findings from the term research project.