Automatically Detecting Architecturally-Relevant Code Anomalies

Abstract — Software architecture degradation is a long-standing problem in software engineering. Previous studies have shown that certain code anomalies- or patterns of code anomalies- are likely to be harmful to architecture design, although their identification is far from trivial. This study presents a system for not only detecting architecturally-relevant code anomalies, but also helping developers to prioritize their removal by ranking them. We detect code anomaly patterns based on static analysis that also exploit architecture information