A Survey of Program Debugging with Interactive Machine Learning

This survey explores how interactive machine learning is used to assist in program debugging. It discusses various techniques where machine learning models learn from developer interactions to identify and fix bugs, predict errors, and suggest code improvements, ultimately enhancing the debugging process. While not directly about Sourcery, it covers the core principles of using AI for code analysis and automated refactoring that underpin the tool's functionality.