One of our software center activities is focused on reducing the effort that the designers spend on code analysis and quality assurance. In this project we are looking at creating a model for high and low quality code – in general.
Now I’ve come across this nice paper about using deep learning for finding whether code is more readable or not: https://doi.org/10.1016/j.infsof.2018.07.006
The paper is written by a research team from City University of Hong Kong and Beijing University of Technology. The paper presents a method that has been evaluated against human reviewers and is based on techniques that require no feature engineering. It shows that it is better than the previous approaches, yet requires less effort to set up.
The paper also provides the possibility to reuse the code – great and very interesting reading.
In Software Center, we create a deep learning model that can learn the quality of code from tools for code review and reduce the review effort by order of magnitude. Please take a look at our presentation from the Software Center Metrics Day.