Automated Detection of Code Smells Using Deep Learning

An automated system that detects code smells using deep learning.

An automated system that detects code smells using deep learning. As a reference project it shows how a system like this is put together in practice, which parts matter and how they are tested, so that a developer can learn from it and build on it.

It suits learners who want to practise engineering discipline: requirements, design, implementation, automated testing and measuring software quality.

The main parts are a clear requirements and design document, the working implementation, automated tests with quality metrics, and a report on what the measurements show. The reference build uses TensorFlow, Python, Git, Docker, and pytest, with a clear project structure, setup instructions and sample data so that it can be run and extended.