Empirical Study of Mis-classification Testing in Open Source Supervised Learning Projects using 278 Python-based open-source software projects that use supervised learning
Software anomalies are typically captured in databases, classified, and traced until they are resolved. These databases then remain part of the history for the space missions to refer to as necessary.
Checklist and data extracted from publications analyzed for "Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review" paper
