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Research has shown that code anomalies may be related to problems in the architecture design. Without proper mechanisms to support the identification of architecturallyrelevant code anomalies, software systems will degrade and might be discontinued as a consequence. Nowadays, metrics-based detection strategy is the most common mechanism to identify code anomalies. However, these strategies often fail to detect architecturally-relevant code anomalies. A key limitation is that they solely exploit measurable static properties of the source code. This paper proposes and evaluates a suite of architecturesensitive detection strategies. These strategies exploit information related to how fully-modularized and widely-scoped architectural concerns are realized by the code elements. The accuracy of the proposed detection strategies is assessed in a sample of nearly 3500 architecturally-relevant code anomalies and 950 architectural problems distributed in 6 software systems. Our findings show that more than the 60% of code anomalies detected by the proposed strategies were related to architectural problems. Additionally, the proposed strategies identified on average 50% more architecturally-relevant code anomalies than those gathered with using conventional strategies.

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