Architecture degradation has a strong negative impact on software quality and can result in significant losses. Severe software degradation does not happen overnight. Software evolves continuously, through numerous issues, fixing bugs and adding new features, and architecture flaws emerge quietly and largely unnoticed until they grow in scope and significance when the system becomes difficult to maintain. Developers are largely unaware of these flaws or the accumulating debt as they are focused on their immediate tasks of address individual issues. As a consequence, the cumulative impacts of their activities, as they affect the architecture, go unnoticed. To detect these problems early and prevent them from accumulating into severe ones, we propose to monitor software evolution by tracking the interactions among files revised to address issues. In particular, we propose and show how we can automatically detect active hotspot, to reveal architecture problems. We have empirically studied hundreds of hotspots along the evolution timelines of 21 open source projects, and showed that there exist just a few dominating active hotspots per project at any given time. Moreover, these dominating active hotspots persist over long time periods, and thus deserve special attention. Compared with state-of-the-art design and code smell detection tools we report that by using active hotspots it is possible to detect signs of software degradation both earlier and more precisely.