This book treats software systems like crime scenes, showing how to use forensic techniques and data from version-control and issue-tracking systems to identify the parts of a codebase that are most risky, most change-prone, and most in need of attention. It explains how to mine temporal and social metadata—who changes what, how often, and in what combinations—to find hotspots, tangled dependencies, and hidden technical debt; introduces concepts such as temporal coupling, code ownership, and developer networks; and shows how visualization, metrics, and small experiments can guide prioritization of refactoring and testing efforts so teams can make evidence-based decisions to reduce maintenance cost and risk.