<p data-start="77" data-end="552">Many teams look at code coverage as a single percentage, but the real insights often come from watching how coverage evolves over weeks and months. Sudden drops, unusual spikes, or long periods of stagnation can all signal deeper issues that a static number won&rsquo;t capture. For instance, a steady decline might indicate that new features are being shipped without corresponding tests, while erratic fluctuations could suggest unstable or brittle test suites. Tracking trends ofcode coverage also helps teams understand whether their testing strategy is keeping pace with development complexity. If coverage plateaus while the codebase grows rapidly, it may be a sign that technical debt is piling up or that testing practices need reinforcement. On the other hand, gradual and consistent improvements often reflect a maturing engineering culture where tests are treated as part of the development flow, not an afterthought. By focusing on patterns instead of snapshots, teams can proactively identify problem areas, plan better refactoring efforts, and create healthier long-term testing habits that support more resilient software.