Automatically detecting architecturally-relevant code anomalies

Abstract

Software architecture degradation is a longstanding 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.