Human-level Ordinal Maintainability Prediction Based on Static Code Metrics
Markus Schnappinger, Arnaud Fietzke, Alexander Pretschner · Evaluation and Assessment in Software Engineering · 2021
One of the greatest challenges in software quality control is the efficient and effective measurement of maintainability. Thorough expert assessments are precise yet slow and expensive, whereas automated static analysis yields imprecise yet rapid feedback. Several machine learning approaches aim to integrate the advantages of both concepts.